Oracle Cloud. Using Oracle Business Intelligence Cloud Service E37397-05

Oracle Cloud Using Oracle Business Intelligence Cloud Service E37397-05 April 2015

Oracle Cloud Using Oracle Business Intelligence Cloud Service, E37397-05 Copyright 2014, 2015, Oracle and/or its affiliates. All rights reserved. Primary Author: Christine Jacobs Contributing Authors: Marla Azriel, Suzanne Gill, Rosie Harvey, Cammy Moore, Lea Shaw Contributors: Oracle Business Intelligence development, product management, and quality assurance teams This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. 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Contents Preface... Audience... Documentation Accessibility... Related Resources... Conventions... xv xv xv xvi xvi What s New in Oracle BI Cloud Service?... xvii Part I Introducing Oracle Business Intelligence Cloud Service 1 Getting Started with Oracle Business Intelligence Cloud Service About Oracle BI Cloud Service... 1-1 About Analyses and Dashboards... 1-2 How to Begin with Oracle BI Cloud Service... 1-3 Typical Workflow for Administrators of Oracle Business Intelligence Cloud Service... 1-4 Before You Begin with Oracle BI Cloud Service... 1-5 How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service?... 1-5 About Oracle BI Cloud Service Roles and Users... 1-6 Accessing Oracle BI Cloud Service... 1-6 Finding and Exploring Your Content... 1-7 Analyzing and Interacting with Information for Insight... 1-8 Using Oracle BI Cloud Service on Mobile Devices... 1-9 Top Tasks for Oracle BI Cloud Service... 1-10 Top Tasks for Exploring... 1-10 Top Tasks for Analyzing... 1-10 Top Tasks for Data Loading... 1-11 Top Tasks for Data Modeling... 1-11 Top Tasks for Managing... 1-12 iii

Part II Exploring Data in Visual Analyzer 2 Getting Started with Visual Analyzer About Visual Analyzer... 2-1 Accessing Visual Analyzer... 2-1 Searching for Content in Visual Analyzer... 2-2 3 Exploring Your Content Typical Workflow for Exploring Content... 3-1 Choosing Data Sources... 3-2 Adding Data Elements to Visualizations... 3-3 Adding Data Elements to Drop Targets... 3-3 Adding Data Elements to Visualization Drop Targets... 3-4 Adding Data Elements to a Blank Canvas... 3-5 Adjusting the Canvas Layout... 3-6 Changing Visualization Types... 3-6 Adjusting Visualization Properties... 3-7 Undoing and Redoing Visualization Edits... 3-8 Reversing Visualization Edits... 3-9 Refreshing Visualization Content... 3-9 Exploring Data Using Filters... 3-9 About Filters... 3-9 About Filter Types... 3-10 About Automatically Applied Filters... 3-10 Creating Filters... 3-11 Applying Range Filters... 3-11 Applying List Filters... 3-11 Applying Date Filters... 3-12 Building Expression Filters... 3-12 Exploring Data in Other Ways... 3-13 About Composing Expressions... 3-14 Creating Calculated Data Elements... 3-14 Specifying How Visualizations Interact with One Another... 3-15 4 Adding Your Own Data Typical Workflow for Adding Data from External Sources... 4-1 About Adding Your Own Data... 4-2 About Characteristics for External Sources... 4-3 Adding Data from External Sources... 4-4 Blending Data that You Added... 4-6 Refreshing Data that You Added... 4-8 Updating Details of Data You Added... 4-9 iv

Controlling Sharing of Data You Added... 4-9 Removing Data that You Added... 4-10 Deleting Data that You Added... 4-10 Part III Reporting Data in Oracle Business Intelligence Cloud Service 5 Creating Analyses Typical Workflow for Creating Analyses... 5-1 Creating Your First Analysis... 5-2 Setting Properties for Columns... 5-4 Applying Formatting to Content... 5-4 Formatting Columns... 5-5 Making Your Analyses Dynamic... 5-7 Setting Default Formats for Your System... 5-9 Exporting Content from Analyses and Dashboards... 5-10 Exporting the Results of Analyses... 5-10 Exporting Dashboards and Dashboard Pages... 5-10 Tips for Exporting... 5-11 Editing Formulas or Calculated Measures... 5-11 Editing the Formula for a Column... 5-12 Editing Calculated Measures... 5-14 Adding Data from External Sources to Analyses... 5-14 Blending Data from External Sources to Analyses... 5-16 Setting Properties for Analyses... 5-16 Setting Your Preferences... 5-18 Advanced Techniques: Importing Formatting from Another Analysis... 5-18 About Applying Formatting from Columns... 5-19 About Applying Formatting from Views... 5-19 About Applying Formatting from Containers... 5-19 Importing Formatting from a Saved Analysis to a Target Analysis... 5-19 Advanced Techniques: Combining Columns to Display Data Differently... 5-20 Advanced Techniques: Examining the Logical SQL Statements for Analyses... 5-21 Advanced Techniques: Referencing Stored Values in Variables... 5-21 About Session Variables... 5-22 About Repository Variables... 5-22 About Presentation Variables... 5-22 About Request Variables... 5-23 About Global Variables... 5-24 Creating Global Variables... 5-24 Syntax for Referencing Variables... 5-25 6 Viewing Data in Different Ways Typical Workflow for Viewing Data in Different Ways... 6-2 v

About Views... 6-2 Adding Views... 6-2 Editing Views... 6-3 Editing Various Types of Views... 6-4 Editing Table and Pivot Table Views... 6-5 Editing Gauge Views... 6-6 Editing Performance Tile Views... 6-8 Editing Trellis Views... 6-9 Editing Treemap Views... 6-14 Editing Narrative Views... 6-15 About Editing Non-Data Views... 6-16 Graphing Data in Analyses... 6-18 Editing Graph Views... 6-18 Zooming and Scrolling in Graphs... 6-19 Formatting the Visual Appearance of Graphs... 6-20 Limiting Data Displayed in Graphs and Gauges... 6-23 Saving Views... 6-24 Rearranging Views... 6-24 Refreshing the Results in Views... 6-25 Printing Views... 6-26 Changing Print Options for Views... 6-26 Previewing How Views Are Displayed on Dashboards... 6-27 Removing Views... 6-27 Sorting Values in Views... 6-28 Clearing Sorts in Views... 6-29 Drilling in Results... 6-29 About Drilling... 6-29 Drilling in Tables and Trellises... 6-30 Drilling in Graphs... 6-31 Resizing Rows and Columns in Views... 6-32 Configuring for Resizing in Views... 6-32 Resizing in Views... 6-32 Suppressing Null Values in Views... 6-33 Assembling Views for Display... 6-34 Linking Views in Master-Detail Relationships... 6-34 Defining Master Views... 6-35 Defining Detail Views... 6-36 Modifying the Layout of Data in Views... 6-37 Adding and Rearranging Columns in Views... 6-37 Setting Properties for Sections of Data in Views... 6-39 Adding Totals to Tables and Pivot Tables... 6-40 Displaying Running Sums and Relative Values in Pivot Tables... 6-41 About Drop Targets in the Layout Pane... 6-42 vi

About the Types of Drop Targets... 6-43 About the Excluded Drop Target... 6-43 About the Guidelines for Drop Targets for Various Views... 6-44 7 Building Dashboards Typical Workflow for Building Dashboards... 7-1 Creating Your First Dashboard... 7-2 Editing Dashboards... 7-3 Adding and Deleting Pages in Dashboards... 7-4 Adding Pages to Dashboards... 7-4 Adding Content to Dashboard Pages... 7-5 Changing the Properties of a Dashboard and Its Pages... 7-5 Changing the Properties of Objects Added to Dashboard Pages... 7-6 Deleting Objects on Dashboard Pages... 7-7 Deleting Dashboard Pages... 7-7 Preparing to Print Dashboards... 7-8 Organizing Dashboard Pages in Briefing Books... 7-8 Adding Content to New or Existing Briefing Books... 7-8 Editing the Content of Briefing Books... 7-9 Downloading Briefing Books... 7-10 Adding a List of Briefing Books to a Dashboard Page... 7-10 Improving the Time to Display Dashboard Pages with Default Selections... 7-11 Recalling Personalized Settings... 7-12 Saving Customizations of Dashboard Pages... 7-12 Applying Saved Customizations... 7-13 Editing Saved Customizations... 7-14 Clearing the Current Customization... 7-14 Linking to Dashboard Pages... 7-14 About Bookmark Links... 7-14 Creating Links to Dashboard Pages... 7-15 8 Filtering and Selecting Data for Analyses Typical Workflow for Filtering and Selecting Data... 8-1 About Filters and Selection Steps... 8-2 About Prompted Filters... 8-2 Creating Filters for Columns... 8-2 Creating Inline and Named Filters... 8-3 Specifying Values for Filters... 8-4 Saving Filters... 8-5 Editing Filters for Columns... 8-6 Reusing Filters... 8-7 Using a Saved Analysis as a Filter... 8-8 Advanced Techniques: How Dashboard Prompts and Analysis Prompts Interact... 8-9 vii

Refining Selections of Data... 8-10 Creating Selection Steps... 8-10 Editing Selection Steps... 8-12 Saving Selection Steps for Reuse... 8-13 Advanced Techniques: Creating Condition Steps... 8-14 Manipulating Members Using Groups and Calculated Items... 8-16 About Groups and Calculated Items... 8-16 Creating Groups and Calculated Items... 8-17 Editing Groups and Calculated Items... 8-18 Viewing Group Contents... 8-19 Saving Groups and Calculated Items... 8-19 Reusing a Group or Calculated Item in an Analysis... 8-20 Deleting Groups and Calculated Items... 8-21 9 Prompting in Analyses and Dashboards Typical Workflow for Prompting in Analyses and Dashboards... 9-1 Creating Prompts... 9-1 Creating Column Prompts... 9-2 Creating Variable Prompts... 9-4 Overriding a Selection Step with a Prompt... 9-5 Editing Column Prompts... 9-6 Adding Prompts to Dashboard Pages... 9-6 10 Making Analyses Interactive Typical Workflow for Making Analyses Interactive... 10-1 Creating Named Actions for Reuse... 10-2 Creating Inline Actions... 10-4 Adding Actions to Analyses... 10-4 Adding Actions to Dashboard Pages... 10-6 Adding Actions to Dashboard Pages Using Action Links... 10-6 Adding Actions to Dashboard Pages Using Action Link Menus... 10-7 Editing Named Actions... 10-8 Editing and Deleting Actions and Action Links Added to Analyses... 10-8 Editing Actions, Action Links, and Action Link Menus Added to Dashboard Pages... 10-9 Saving Inline Actions in Analyses to the Catalog... 10-10 Saving Inline Actions in Dashboards to the Catalog... 10-11 11 Managing Content Typical Workflow for Managing Content... 11-1 Renaming Content... 11-1 Renaming Items... 11-2 Renaming Views... 11-2 Accessing Favorites Easily... 11-2 viii

Adding Favorites... 11-2 Removing Favorites... 11-3 Accessing Properties... 11-3 Sharing Your Content with Others... 11-4 Sharing Items... 11-4 Sharing Dashboard Sections... 11-6 Assigning Ownership of Items... 11-6 Assuming Ownership of Items... 11-7 Part IV Loading Data in Oracle Business Intelligence Cloud Service 12 Getting Your Data to the Cloud Uploading Your Data to the Cloud... 12-1 13 Loading Data from Files Typical Workflow for Loading Files... 13-1 About Data Loader... 13-1 About Column Types... 13-2 Transforming Your Data... 13-3 Loading Your Files into a New Table... 13-3 Loading Your Files into an Existing Table... 13-5 Viewing Data Load History... 13-7 Correcting Errors in Data Loads... 13-9 14 Loading Data from Relational Tables Loading Relational Tables Using SQL Developer... 14-1 Loading On-Premises Relational Sources and Files to the Cloud Using Oracle BI Cloud Service Data Sync... 14-2 15 Automating Loading Data Using Programmatic Methods About the Oracle BI Cloud Service REST API... 15-1 About the Oracle Database Cloud Service REST API... 15-1 About PL/SQL Database Scripts... 15-2 Part V Modeling Data in Oracle Business Intelligence Cloud Service 16 Understanding Data Modeling About Modeling Data... 16-1 Planning a Data Model... 16-2 Understanding Data Model Requirements... 16-2 Components of Data Models... 16-2 About Modeling Source Objects with Star Relationships... 16-3 About Modeling Source Objects with Snowflake Relationships... 16-4 ix

About Modeling Denormalized Sources... 16-4 About Modeling Normalized Sources... 16-4 Roadmap for Modeling Data... 16-5 17 Starting to Build Your Data Model Typical Workflow for Starting a Data Model... 17-1 Using Data Modeler... 17-2 Opening Data Modeler... 17-2 Using the Left Pane in Data Modeler... 17-2 Using the Right Pane in Data Modeler... 17-3 Using Action Menus... 17-4 Locking the Data Model... 17-5 Validating the Data Model... 17-5 Refreshing and Synchronizing Source Objects and Data Model Objects... 17-6 Publishing Changes to the Data Model... 17-7 Clearing Cached Data... 17-8 Deleting the Data Model... 17-8 Renaming the Data Model... 17-9 Reviewing Source Tables and Data... 17-9 Viewing Source Objects... 17-9 Previewing Data in Source Objects... 17-9 Creating Source Views... 17-10 About Source Views... 17-10 Adding Your Own Source Views... 17-11 Defining Filters for Source Views... 17-13 Adding Fact Tables and Dimension Tables to the Data Model... 17-13 About Fact Tables and Dimension Tables... 17-14 Creating Fact and Dimension Tables from a Single Table or View... 17-14 Creating Fact Tables Individually... 17-16 Creating Dimension Tables Individually... 17-17 Editing Fact Tables and Dimension Tables... 17-18 Adding More Columns to Fact and Dimension Tables... 17-20 Joining Tables in the Data Model... 17-21 About Joins... 17-21 Joining Fact and Dimension Tables... 17-22 Creating a Time Dimension... 17-22 Using Columns in the Data Model... 17-24 Editing Columns... 17-24 Specifying Aggregation for Measures in Fact Tables... 17-25 Creating Calculated Measures... 17-26 Creating Derived Attributes... 17-29 Creating Expressions in the Expression Editor... 17-29 Copying Columns... 17-31 x

Copying Model Objects... 17-31 18 Defining Hierarchies and Levels for Drilling and Aggregation Typical Workflow for Defining Hierarchies and Levels... 18-1 About Hierarchies and Levels... 18-1 Editing Hierarchies and Levels... 18-2 Setting Dimension Table Properties for Hierarchies... 18-3 Setting Aggregation Levels for Measures... 18-4 About Setting Aggregation Levels for Measures... 18-4 19 Securing Your Data Model Typical Workflow for Securing Your Data... 19-1 Creating Variables to Use in Expressions... 19-1 About Variables... 19-2 Defining Variables... 19-2 Securing Access to Objects in the Model... 19-4 About Permission Inheritance... 19-5 Defining Data Security Filters... 19-5 Part VI Managing Oracle Business Intelligence Cloud Service 20 Managing What Users Can See and Do Typical Workflow for Managing What Users See and Do... 20-1 About Users and Roles... 20-1 About Application Roles... 20-2 Application Roles Predefined in Oracle BI Cloud Service... 20-2 Configuring What Users Can See and Do... 20-4 Getting Started with Application Role Management... 20-4 Assigning Members and Actions to Application Roles... 20-5 Why is Membership of the BI Service Administrator Application Role Important?... 20-6 Assigning Application Roles to Users... 20-7 Assigning Application Roles to User Roles... 20-7 Adding Your Own Application Roles... 20-8 Exiting the Service Console... 20-9 Functionality Enabled by Application Roles... 20-10 21 Backing Up and Restoring Typical Workflow for Backing Up and Restoring... 21-1 About Snapshots... 21-1 Taking Snapshots and Restoring Information... 21-2 Taking a Snapshot... 21-2 Restoring from a Snapshot... 21-3 Editing Snapshot Descriptions... 21-4 xi

Deleting Snapshots... 21-4 Downloading, Uploading, and Migrating Snapshots... 21-5 Downloading Snapshots... 21-5 Uploading Snapshots... 21-6 Migrating Snapshot Data... 21-7 22 Performing Administration Tasks Typical Workflow for Performing Administration Tasks... 22-1 Understanding Administration Tools... 22-2 Changing the Database Connection... 22-2 Uploading Data Models from a File (.rpd)... 22-3 About Uploading Data Models to the Cloud... 22-3 Uploading Data Models to the Cloud... 22-5 Managing Session Information in Oracle BI Cloud Service... 22-6 Monitoring Users Who Are Signed In... 22-6 Analyzing SQL Queries and Logs... 22-6 Executing Test SQL Queries... 22-8 Monitoring Metrics for Oracle BI Cloud Service... 22-8 Part VII Reference A Terminology B Frequently Asked Questions for Oracle Business Intelligence Cloud Service Top FAQs for Analyses and Dashboards... B-2 Top FAQs for Data Loading... B-3 Top FAQs for Data Modeling... B-4 Top FAQs for Managing Oracle BI Cloud Service... B-5 C Troubleshooting Oracle Business Intelligence Cloud Service Troubleshooting General Issues... C-2 Troubleshooting Issues with Analyses and Dashboards... C-2 Troubleshooting Data Loading Issues... C-3 Troubleshooting Data Modeling Issues... C-4 Troubleshooting Administration Issues... C-5 D Expression Editor Reference Data Model Objects... D-1 SQL Operators... D-1 Conditional Expressions... D-2 Functions... D-2 Aggregate Functions... D-3 Calendar Functions... D-3 xii

Conversion Functions... D-5 Display Functions... D-5 Evaluate Functions... D-6 Mathematical Functions... D-7 String Functions... D-8 System Functions... D-9 Time Series Functions... D-9 Constants... D-10 Types... D-10 Variables... D-10 E Accessibility About Accessibility Features... E-1 Changing to Accessibility Mode... E-1 About Keyboard Shortcuts... E-2 Navigating with Keystrokes... E-3 Navigating on the Home Page... E-4 Navigating in Dashboards... E-4 xiii

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Preface Learn how to use the service to explore, load, model, and analyze data by creating and editing projects and reports, and administer users. Topics: Audience Documentation Accessibility Related Documents Conventions Audience Using Oracle Business Intelligence Cloud Service is intended for anyone who plans to use Oracle BI Cloud Service: analysts, data handlers, and application developers. Business intelligence analysts, who explore, create, manage, and organize analyses and projects and who run, share, and interact with analyses. It also includes users who view business intelligence data on a mobile device. Data handlers, who create connections to data sources, upload data from sources, build data models, and control user access to data. Application developers, data service providers, and middle-tier administrators who want to programmatically access and use Oracle BI Cloud Service to create applications or integrations with other components. Documentation Accessibility For information about Oracle's commitment to accessibility, visit the Oracle Accessibility Program website at http://www.oracle.com/pls/topic/lookup? ctx=acc&id=docacc. Access to Oracle Support Oracle customers that have purchased support have access to electronic support through My Oracle Support. For information, visit http://www.oracle.com/pls/ topic/lookup?ctx=acc&id=info or visit http://www.oracle.com/pls/ topic/lookup?ctx=acc&id=trs if you are hearing impaired. xv

Related Resources These related Oracle resources provide more information. Oracle Public Cloud http://cloud.oracle.com Getting Started with Oracle Cloud Conventions The text conventions used in this document are described in this topic. Convention boldface italic monospace Meaning Boldface type indicates graphical user interface elements associated with an action, or terms defined in text or the glossary. Italic type indicates book titles, emphasis, or placeholder variables for which you supply particular values. Monospace type indicates commands within a paragraph, URLs, code in examples, text that appears on the screen, or text that you enter. xvi

What s New in Oracle BI Cloud Service? Anyone who subscribes to Oracle BI Cloud Service receives automatic upgrades as soon as new features become available. You don't need to request an upgrade or take any actions yourself. Here s an overview of new features and enhancements added recently to improve your Oracle BI Cloud Service experience. April 2015 Integrate with Oracle Database Cloud Service (Database as a Service) Connect Oracle BI Cloud Service to any Oracle Database Cloud Service (Database as a Service) instance. See Changing the Database Connection. Upload data models from a file If you ve modeled your data with Oracle Business Intelligence Enterprise Edition, then you don't need to start from scratch in Oracle BI Cloud Service. Simply upload your on-premises data model file (.rpd) to Oracle BI Cloud Service and start exploring your data through visualizations, reports, and dashboards. See Uploading On-Premises Data Models. Add your own data to analyses You can add data from an external source to an analysis in Oracle BI Cloud Service. Adding your own data is sometimes referred to as mash-up. See Adding Data from External Sources to Analyses. Explore data using Visual Analyzer Visual Analyzer provides self-service analysis, seamlessly transitioning you between all phases of the analysis lifecycle: data staging, analysis, composition, and consumption. See Getting Started with Visual Analyzer. Manage access to Visual Analyzer through a new application role called BIDiscoveryContentAuthor. See Application Roles Predefined in Oracle BI Cloud Service. March 2015 Loading Data Load data programmatically Use methods of REST APIs to programmatically create, manage, and load schemas, tables, and data into Oracle BI Cloud Service. About the Oracle BI Cloud Service REST API xvii

February 2015 Modeling Data Copy objects in Data Modeler Sometimes it s quicker to copy objects rather than starting from scratch. You can copy fact tables, dimension tables, database tables, and database views. Copying Model Objects Drag and drop to extend dimensions We ve made it easier to add columns to dimension tables. Simply drag and drop tables or views that contain columns that you want to add to the dimension table. Adding Columns from Another Source to a Dimension Table Aggregate before or after calculating the expression for a measure You can create calculations that contain pre-aggregated measures. About Creating Calculated Measures Use fact tables indirectly joined through dimension tables in expressions When you define a calculated measure in Expression Editor, the Expression Elements section includes the current fact table, any dimension tables joined to that table, and any fact tables indirectly joined through a dimension table. About the Expression Editor Data Modeler detects relationships and suggests facts and dimensions for your model When you add source objects with relationships to other tables or views to the model, Data Modeler asks whether you want to include related fact or dimension tables and offers to add them to the model. xviii

Part I Introducing Oracle Business Intelligence Cloud Service This part introduces you to Oracle BI Cloud Service. Chapters: Getting Started with Oracle Business Intelligence Cloud Service

1 Getting Started with Oracle Business Intelligence Cloud Service This topic describes how to get started with Oracle BI Cloud Service. Topics: About Oracle BI Cloud Service About Analyses and Dashboards How to Begin with Oracle Business Intelligence Cloud Service Typical Workflow for Administrators of Oracle BI Cloud Service Accessing Oracle BI Cloud Service Finding and Exploring Your Content Analyzing and Interacting with Information for Insight Using Oracle BI Cloud Service on Mobile Devices Top Tasks for Oracle BI Cloud Service About Oracle BI Cloud Service Oracle BI Cloud Service is one of the Platform as a Service (PaaS) services that is provided by Oracle Cloud. The service simplifies both the preparation of data for reporting and the creation, management, and deployment of analyses. The service offers many self-service capabilities such as creating reports for your line of business. The report consumption features of the service are natively mobile. You can find more information on Oracle BI Cloud Service here: https://cloud.oracle.com/business_intelligence Using Oracle BI Cloud Service, you can easily and efficiently: Load, model, and manage data. Data Loader and Data Modeler enable you to load and model the data that is needed to produce analyses. For more information, see Loading Data in Oracle Business Intelligence Cloud Service and Modeling Data in Oracle Business Intelligence Cloud Service. Explore data and add your own data from external sources. For more information, see Exploring Data in Visual Analyzer. Getting Started with Oracle Business Intelligence Cloud Service 1-1

About Analyses and Dashboards Create and share analyses and dashboards that enable users to solve business problems. For more information, see Reporting Data in Oracle Business Intelligence Cloud Service. Manage and secure the service. The Service Console enables administrators to manage what users can see and do in Oracle BI Cloud Service, back up and restore content, and more. For more information, see Managing Oracle Business Intelligence Cloud Service. About Analyses and Dashboards You use analyses and dashboards to find the answers that you need from key business data displayed in graphical formats. An analysis is a query against your organization's data that provides you with answers to business questions. Analyses enable you to explore and interact with information visually in tables, graphs, pivot tables, and other data views. You can also save, organize, and share the results of analyses with others. Dashboards can include multiple analyses to give you a complete and consistent view of your company s information across all departments and operational data sources. Dashboards provide you with personalized views of information in the form of one or more pages, with each page identified with a tab at the top. Dashboard pages display anything that you have access to or that you can open with a web browser including analyses results, images, text, links to websites and documents, and embedded content such as web pages or documents. 1-2 Using Oracle Business Intelligence Cloud Service

How to Begin with Oracle BI Cloud Service When you embed an analysis in a dashboard, the analysis automatically displays the most current data every time you access the dashboard. For example, if you are a sales executive whose company captures sales data on a daily basis, then you can have the dollar volume by product sold today displayed when you open or run the dashboard. For more information about sharing analyses and dashboards, see Sharing Your Content with Others. How to Begin with Oracle BI Cloud Service Oracle BI Cloud Service offers features for different kinds of users who perform various tasks. The largest user population is end users who are given an address and their sign-on credentials for accessing the service and analyses and dashboards. Before users can sign in, administrators must have configured the user population, loaders must have loaded the data into Oracle Database Cloud Service (Database Schema), and modelers must have modeled the data. When data is modeled, users can create analyses and dashboards that allow them to glean important information about their business. Task User More Information Access the service. All Accessing Oracle BI Cloud Service Getting Started with Oracle Business Intelligence Cloud Service 1-3

Typical Workflow for Administrators of Oracle Business Intelligence Cloud Service Task User More Information Configure the service for users. Load data from various sources into Oracle Database Cloud Service for use in creating analyses. Model the data after loading it, so users can include the data in analyses. Create analyses that show the data in views on dashboards. Share these analyses with coworkers, clients, and business partners. Filter the data in the analyses. Add views to the analysis. Add interactivity to the analysis. Create prompts to drive the display of data in the analyses on dashboard pages. Build interactive dashboards for users to analyze data. Find and explore content. Analyze information for insight. Manage the users and roles for the service. Administrators Data loaders Data modelers Content developers Content developers Content developers Content developers Content developers Content developers Content developers and content consumers Content consumers Administrators Typical Workflow for Administrators of Oracle BI Cloud Service Loading Data into a New Table Roadmap for Modeling Data Creating Your First Analysis Creating Filters for Columns Adding Views Adding Interactivity to Analyses Creating Prompts Creating Your First Dashboard Finding and Exploring Your Content Analyzing and Interacting with Information for Insight Managing Oracle Business Intelligence Cloud Service Typical Workflow for Administrators of Oracle Business Intelligence Cloud Service Here are the common tasks to administer Oracle Business Intelligence Cloud Service. Task Description More information Start trial and paid services Provide your information and sign up for a free trial service, or request a paid service. Requesting a Trial Subscription or Purchasing a Subscription to an Oracle Cloud Service section in Getting Started with Oracle Cloud 1-4 Using Oracle Business Intelligence Cloud Service

Typical Workflow for Administrators of Oracle Business Intelligence Cloud Service Task Description More information Activate trial and paid services Access the service After Oracle provisions your service, sign in and activate it. Access Oracle Business Intelligence Cloud Service. Activating Your Trial Subscription or Activating Your Order for an Oracle Cloud Service section in Getting Started with Oracle Cloud Accessing Oracle BI Cloud Service Add and manage users Create accounts for your users. Managing Users and Roles section in Getting Started with Oracle Cloud Monitor service Manage the service Upsize your service subscription Check on the day-to-day operation of your service, monitor performance, and review important notifications. Manage Oracle Business Intelligence Cloud Service including users, backups, and database connections. Add capacity to your existing paid service by upsizing it to a higher subscription level. My Account versus My Services in Getting Started with Oracle Cloud Managing Oracle Business Intelligence Cloud Service Changing Your Paid Subscription to an Oracle Cloud Service in Getting Started with Oracle Cloud Before You Begin with Oracle BI Cloud Service Administrators must ready Oracle BI Cloud Service for others to use. Before you allow users to sign in to Oracle BI Cloud Service, familiarize yourself with: Oracle Cloud Create and configure your account on Oracle Cloud. For more information about creating an account on Oracle Cloud, see the Requesting a Trial Service or Ordering an Oracle Cloud Service section in Getting Started with Oracle Cloud. Oracle Database Cloud Services You need Oracle Database Cloud Service (Database Schema) or Oracle Database Cloud Service (Database as a Service) to store and manage the data that you use in Oracle BI Cloud Service. See How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service? How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service? You need a database to store and manage the data that you use in Oracle BI Cloud Service. Oracle BI Cloud Service can integrate with Oracle Database Cloud Service (Database Schema) or Oracle Database Cloud Service (Database as a Service): Oracle Database Cloud Service (Database Schema) Single schema-based service, included with Oracle BI Cloud Service. Oracle BI Cloud Service comes integrated with Oracle Database Cloud Service (Database Schema) so there s no extra step if you want to use this database. See also Using Oracle Database Cloud Service (Database Schema). Oracle Database Cloud Service (Database as a Service) Dedicated virtual machine with a fully configured, running Oracle Database instance. Getting Started with Oracle Business Intelligence Cloud Service 1-5

Accessing Oracle BI Cloud Service You can configure Oracle BI Cloud Service to use Oracle Database Cloud Service (Database as a Service). If you want to integrate with Oracle Database Cloud Service (Database as a Service), your administrator must provide connection details. See Changing the Database Connection. See also Using Oracle Database Cloud Service (Database as a Service). Note: Similar to Oracle Database Cloud Service, Oracle BI Cloud Service uses the concepts of column and table. See Terminology for important information on how Oracle BI Cloud Service uses these terms. About Oracle BI Cloud Service Roles and Users Before users can begin accessing Oracle BI Cloud Service, you as the administrator must ensure that roles and privileges for users are properly configured. See the Oracle Cloud User Roles and Privileges section in Getting Started with Oracle Cloud for information on roles and privileges that are common across Oracle Cloud services. The features that you can access in Oracle BI Cloud Service depend on the application roles that you have been assigned. See Functionality Enabled by Application Roles to learn which features are available to each application role. Accessing Oracle BI Cloud Service When you have subscribed to Oracle BI Cloud Service, you can access it directly from a link provided by the service administrator. Or you can sign in to Oracle Cloud and select Oracle BI Cloud Service at this location: cloud.oracle.com When you sign in to Oracle BI Cloud Service for the first time, Oracle Cloud displays the product tour, which provides helpful information on using the service. At the end of the tour, you see the Home page for Oracle BI Cloud Service. The branding bar at the top of the page identifies the user who has signed in and includes the Sign Out link. From the Home page, you can access the various features for which you have the appropriate privileges. 1-6 Using Oracle Business Intelligence Cloud Service

Finding and Exploring Your Content Finding and Exploring Your Content You can find the reports and other items that you access frequently on the Home page and in the catalog. Video Tutorial The catalog contains content that you or someone else defined and saved for future use (such as analyses and dashboards). You can search your content to find something that you want to work with or change. You can edit items, share them with others, access their properties, and so on. For example, a sales analyst needs to use an analysis to track the weekly sales of a specific beverage brand in the Central and Eastern regions. The catalog administrator gives the analyst the appropriate permissions for completing tasks on the targeted content. To manage your content: 1. On the Home page, click the item that you want to access, if you see a link to the item there. Or click Explore Your Catalog to search for the item. 2. On the Catalog page, click Search to display the Search pane. 3. In the Search pane, set up your search. Getting Started with Oracle Business Intelligence Cloud Service 1-7

Analyzing and Interacting with Information for Insight Criterion Search Location Type Description Specify the full or partial name of the item or folder that you are looking for. The search is case-insensitive. Enter an asterisk (*) in the search string to perform a wildcard search. The asterisk specifies zero or more alphanumeric characters within the name. For example, to search for objects that have the word "brand" in their name, specify br* Select the catalog folder to search, such as Company Shared. Select the kind of item that you are looking for, such as Analysis or Dashboard. 4. To search for Hidden Items, select Show Hidden Items, which is located on the header of the Catalog page. 5. Click Search. The Catalog area shows you the items for which you have appropriate permissions and that satisfy the search criteria. 6. When you find the item that are looking for, you can perform tasks on it: a. Edit the item. b. Share the item with others. For information, see Sharing Your Content with Others. c. Access the properties of the item. For information, see Accessing Properties. d. Assign ownership of the item. For information, see Assigning Ownership of Items. Analyzing and Interacting with Information for Insight You use Oracle BI Cloud Service to create analyses of your data. When an analysis is built, you can share it with others, who then interact with the data and analyze the data for insight. By focusing on the data values, users can glean important information about the state of the company or their products. For example, users can pivot the data. They can drill in the data to see greater detail. You can obtain a sample application called QuickAnalytics that provides prebuilt analyses and dashboards. These samples give you ideas and a starting point for creating your own analyses and dashboards. You can obtain QuickAnalytics from Oracle Technology Network: http://oracle.com/technetwork/middleware/bi-foundation/obieesamples-167534.html 1-8 Using Oracle Business Intelligence Cloud Service

Using Oracle BI Cloud Service on Mobile Devices Using Oracle BI Cloud Service on Mobile Devices You can easily access Oracle BI Cloud Service analyses and dashboards through Oracle Business Intelligence Mobile. You see the same content, and it is optimized for viewing on your mobile device. You can install Oracle Business Intelligence Mobile on your mobile device from the Apple App Store and from the Google Play Store. To install and configure Oracle Business Intelligence Mobile for analyses and dashboards from Oracle BI Cloud Service: 1. Search the Apple App Store or the Google Play Store for "Oracle". 2. Select the "Oracle BI Mobile HD" application (for Apple) or the Oracle BI Mobile application (for Google), and tap the Install button. 3. On your device's Home screen, tap the Oracle BI Mobile icon. The end-user licensing agreement screen is displayed. 4. Scroll to read the licensing agreement, and if you agree to the terms, tap Accept. 5. On the Login screen or the Connections screen, tap the Add Server row (with the plus sign) or the Add button (the circled plus sign) to enter your initial server configuration settings. 6. In the Server Settings screen or the Connections screen, specify the following details. Contact your administrator for assistance in completing the fields. Setting Name or Nickname Host Port SSL SSO Username Password Save Password Device Locale Description Give the server connection a name. Once you specify this name, you cannot change the name later. Enter the name of the server to connect to. Enter either the IP address (for example: 192.168.1.1) or the fully qualified host name of the computer on which Oracle BI Presentation Services is running (for example, host1.analytics.us2.oraclecloud.com). Do not enter a stand-in URL, such as tinyurl.com/1234 that redirects to a server. Enter the port number (for example, 443). Generally, you can accept the default value. Leave this set to ON. The Secure Sockets Layer (SSL) protocol is configured on the entry point for the server for Oracle Business Intelligence Presentation Services by the system administrator. Leave this set to ON. Single Sign-On (SSO) is configured on the entry point for the server for Oracle Business Intelligence Presentation Services by the system administrator. Accept the default value. You are prompted for your user name when you start to connect to the server. Accept the default value. You are prompted for your user name when you start to connect to the server. Accept the default value. Accept the default value. Getting Started with Oracle Business Intelligence Cloud Service 1-9

Top Tasks for Oracle BI Cloud Service Setting Description Analytics Path Enter the path for starting Oracle BI Cloud Service(for example, / analytics/saw.dll). Generally, you can accept the default value. 7. On an Apple device, tap Save, then tap Login. 8. On an Android device, tap Test Connection if you want to try the server connection. Then tap Done. Once you are signed in on an Apple device, you can modify your server configuration or add a new server connection by tapping the Options icon (in the branding bar) and then Settings. Once you are signed in on an Android device, you can modify your server configuration or add a new server connection by tapping the Menu icon (the three stacked squares), then Connections. For information about using Oracle BI Cloud Service on mobile devices, see the Oracle Business Intelligence Mobile Help system that is available from within the mobile application. Top Tasks for Oracle BI Cloud Service In Oracle BI Cloud Service, there are top tasks for exploring, analyzing, data loading, data modeling, and managing. Tasks: Top Tasks for Exploring Top Tasks for Analyzing Top Tasks for Exploring Top Tasks for Analyzing Top Tasks for Data Loading Top Tasks for Data Modeling Top Tasks for Managing The top tasks for exploring are identified in this topic. Choosing Data Sources Adding Data Elements to Visualizations Exploring Data Using Filters Adding Data from External Sources The top tasks for analyzing are identified in this topic. Finding and Exploring Your Content Creating Your First Analysis Creating Your First Dashboard 1-10 Using Oracle Business Intelligence Cloud Service

Top Tasks for Oracle BI Cloud Service Adding Interactivity to Analyses Formatting Columns Exporting Content from Analyses and Dashboards Adding Views Adding Content to Dashboard Pages Creating Column Prompts Top Tasks for Data Loading Top Tasks for Data Modeling Adding Prompts to Dashboard Pages The top tasks for data loading are identified in this topic. Loading Your Files into a New Table Loading Your Files into an Existing Table Correcting Errors in Data Loads Loading Relational Tables Using SQL Developer Loading On-Premises Relational Sources and Files to the Cloud Using Oracle BI Cloud Service Data Sync Automating Loading Data Using Programmatic Methods The top tasks for data modeling are identified in this topic. Reviewing Source Tables and Data Adding Your Own Source Views Creating Fact and Dimension Tables from a Single Table or View Creating Fact Tables Individually Creating Dimension Tables Individually Joining Fact and Dimension Tables Creating Calculated Measures Creating Derived Attributes Creating a Time Dimension Editing Hierarchies and Levels Securing Access to Objects in the Model Publishing Changes to the Data Model Getting Started with Oracle Business Intelligence Cloud Service 1-11

Top Tasks for Oracle BI Cloud Service Top Tasks for Managing The top tasks for managing Oracle BI Cloud Service are identified in this topic. Assigning Members and Actions to Application Roles Assigning Application Roles to Users Assigning Application Roles to User Roles Adding Your Own Application Roles Taking a Snapshot Restoring from a Snapshot Downloading Snapshots Changing the Database Connection Uploading Data Models from a File (.rpd) 1-12 Using Oracle Business Intelligence Cloud Service

Part II Exploring Data in Visual Analyzer This part explains how to explore data in Visual Analyzer. Chapters: Getting Started with Visual Analyzer Exploring Your Content Adding Your Own Data

2 Getting Started with Visual Analyzer This topic describes how to get started with Visual Analyzer. Video Topics: About Visual Analyzer Accessing Visual Analyzer Searching for Content in Visual Analyzer About Visual Analyzer Oracle Business Intelligence Cloud Service Visual Analyzer is a web-based tool that enables you to explore Oracle analytics data visually and on an individual basis. Creating visualizations is easy in Visual Analyzer in that your data analysis work becomes more of an individual experience in exploration and discovery rather than an extended process of constructing views from data. Visual Analyzer enables you to experiment with a wealth of different options for how to view your data, and in this experimentation process, you find correlations, discover patterns, and see trends in your content. In Oracle BI Cloud Service, you can create detailed analyses and carefully curated dashboards but Visual Analyzer provides you with a set of end-user tools for faster, simpler assembly of detailed reports arranged together in an appealing, meaningful display. Visual Analyzer goes even further to give you dynamic views for focused, exploratory interaction with your data. In addition, with Visual Analyzer s capability to load external data sources, you get self-service data blending of governed enterprise data with your own files. Accessing Visual Analyzer You access Visual Analyzer from the Home page of Oracle BI Cloud Service. From the Home page of Oracle BI Cloud Service, you can access Visual Analyzer in one of multiple ways: Click Create a Visual Analyzer Project in the left pane. From the New menu, click Project. In the thumbnails, click a Visual Analyzer project to open it. Getting Started with Visual Analyzer 2-1

Searching for Content in Visual Analyzer Visual Analyzer is designed for viewing both at a desk and on the move. You can work with Visual Analyzer in the Safari browser on the ipad and iphone. Searching for Content in Visual Analyzer Visual Analyzer enables you to quickly and easily search for content to use in projects. Just enter the characters in a Search field, and Visual Analyzer automatically begins the search. For example, you can use the Search field in the Data Elements pane to find all data elements that contain the word Number. Visual Analyzer returns matching results that are included in the data sources associated with the project. You can also use the Search field in the Data Sources pane to search for data source names, as well as in the Visualizations pane to search for visualization names. 2-2 Using Oracle Business Intelligence Cloud Service

3 Exploring Your Content This topic describes how to explore content in Visual Analyzer. Video Tutorial Topics: Typical Workflow for Exploring Content Choosing Data Sources Adding Data Elements to Visualizations Adjusting the Canvas Layout Changing Visualization Types Adjusting Visualization Properties Undoing and Redoing Edits Reversing Visualization Edits Refreshing Visualization Content Exploring Data Using Filters Exploring Data in Other Ways About Composing Expressions Creating Calculated Data Elements Specifying How Visualizations Interact with One Another Typical Workflow for Exploring Content Here are the common tasks for exploring content in Visual Analyzer. Task Description More Information Select data sources Add data elements Select subject areas or external data sources for a project. Add data elements from a selected data source to visualizations. Choosing Data Sources Adding Data Elements to Visualizations Exploring Your Content 3-1

Choosing Data Sources Task Description More Information Adjust the canvas layout Filter content Set visualization interaction properties Add, remove, and rearrange visualizations. Streamline the content shown in visualizations. Specify how visualizations synchronize. Adjusting the Canvas Layout Exploring Data Using Filters Specifying How Visualizations Interact with One Another Choosing Data Sources Before you can begin to explore data in a project, you must select the source for that information. For example, if you want to explore product sales by region, you can select the Sample Sales subject area as the data source. You can select subject areas or external sources such as excel spreadsheets as your data sources. To choose data sources in a project: 1. In the Add Data Source dialog, select a subject area, saved file, or upload a file that contains the measures and attributes you want to use in your visualizations. This dialog launches automatically when you create a new project. 2. Click OK. Note: To include additional data sources in an existing project, click the Data Sources shelf tab, and then click the Add Data Source link to launch the Add Data Source dialog. 3-2 Using Oracle Business Intelligence Cloud Service

Adding Data Elements to Visualizations Adding Data Elements to Visualizations This topic describes how you add data elements to visualizations in Visual Analyzer. Topics: Adding Data Elements to Drop Targets Adding Data Elements to Visualization Drop Targets Adding Data Elements to a Blank Canvas Adding Data Elements to Drop Targets After you select the data sources for your project, you can begin to add data elements such as measures and attributes to visualizations. The Explore pane contains drop targets and data elements associated with the active visualization in the canvas. The active visualization is outlined in blue, and you can activate a visualization simply by clicking on it. Note: To toggle the Explore pane on or off, click the Explore button on the project toolbar. Here are some of the ways you can add data elements to drop targets: Click the Data Elements shelf tab, and then drag and drop one or more data elements to drop targets in the Explore pane. You can also double click data elements in the shelf to add them. Visual Analyzer automatically positions the data elements in the best drop target in the Explore pane, and it may also change the visualization type to optimize the visualization layout. Exploring Your Content 3-3

Adding Data Elements to Visualizations Note: You can use the Ctrl key to select multiple data elements at a time. You can replace a data element in the Explore pane by dragging it from the shelf and dropping it over an existing data element already in the pane. You can swap data elements in the Explore pane by dragging a data element already inside the pane and dropping it over another data element in the pane. You can remove a data element from the Explore pane by clicking the X in the data element token. Note: If you add an attribute to the Color drop target, it renders discrete colors in the canvas, whereas if you add a measure to that drop target, it only renders shades of a single color. When you perform these same actions on a Pivot visualization, the result is a heat map. If you add multiple measures to the Values drop target, most of the visualizations render in a discrete color for each measure. Adding Data Elements to Visualization Drop Targets You can use visualization drop targets to help you position data elements in the optimal locations for exploring content. If you drag and drop a data element over to a visualization (but not on a specific drop target), Visual Analyzer shows you a blue outline around the recommended drop targets (Columns as shown below) in the visualization. If you drop the data element in the visualization, it is automatically shuttled to the best drop target. Also, you see a green plus icon next to the data element when it is over a valid drop target. 3-4 Using Oracle Business Intelligence Cloud Service

Adding Data Elements to Visualizations Note: If you are not sure where to drag and drop any data element, simply drag and drop the data element anywhere over the visualization, and not to a specific drop target. Visual Analyzer automatically adds it to the best drop target in the canvas. After you drop data elements into visualization drop targets or when you move your cursor outside of the visualization, the drop targets disappear. To display the drop targets again in the visualization, in the visualization toolbar, click Assignment. You can also do this to keep the visualization drop targets in place while you work. For more information on adding, removing, or moving data elements, see Adding Data Elements to Drop Targets. Adding Data Elements to a Blank Canvas You can add data elements directly from the Data Elements pane to a blank canvas. If you drag one or more data elements to a blank canvas or between visualizations in the canvas, Visual Analyzer automatically creates a new visualization and selects the best visualization type and layout. For example, if you add time and product attributes, and a revenue measure to a blank canvas, Visual Analyzer places the data elements in the best locations and selects the visualization type of Line. Exploring Your Content 3-5

Adjusting the Canvas Layout Note: If there are visualizations already in the canvas, you can drag and drop data elements between them. Adjusting the Canvas Layout You can adjust the look and feel of visualizations in the canvas to make them more visually attractive. For example, you can create a visualization and then copy it to the canvas. You can then modify the data elements in the duplicated visualization, change the visualization type, and then resize it. Here are some of the ways that you can adjust the canvas layout: To add additional visualizations to the canvas, click the Visualizations shelf tab, and drag and drop a visualization type from the Visualizations pane to the canvas. Alternatively, on the project toolbar, click Add Visualization. You can then position the new visualization adjacent to a single visualization or spanning multiple ones. To delete a visualization from the canvas, right-click it, and then select Delete. To rearrange a visualization in the canvas, drag and drop the visualization to the location (the space between visualizations) where you want it to go. The target drop area is highlighted in blue. To resize a visualization, use your cursor to drag the edges to size it. To copy a visualization in the canvas, right-click it, and then select Copy. To paste a copied visualization in the canvas, right-click the canvas, and then select Paste. Changing Visualization Types You can change visualization types to maximize the graphical representation of the data you are exploring. Visual Analyzer automatically selects the visualization type based on the selected data elements. However, this is only true when you create a new visualization by dragging data elements to a blank area in the canvas. Once a visualization is created, dragging additional data elements to it won t change the visualization type automatically. 3-6 Using Oracle Business Intelligence Cloud Service

Adjusting Visualization Properties To change visualization types: 1. Select a visualization in the canvas, and in the visualization toolbar, click Visualization Type. Note: You can also add a new visualization to the canvas by dragging it from the Visualizations pane to the canvas. 2. In the View Select dialog, select a visualization type. For example, change the visualization type from Bar to Stacked Bar. Note: You can choose any visualization type, but the visualization types that are displayed in blue are the recommended ones based on the data elements you select and where they are positioned in the canvas. When you change the visualization type, the data elements are moved to matching drop target names. If an equivalent drop target does not exist for the new visualization type, then the data elements are moved to a drop target labeled Unused. You can then move them to the drop target you prefer. Adjusting Visualization Properties You generally don t need to make changes to the properties of your visualizations, because Visual Analyzer sets them for you automatically. You might want to make adjustments such as hiding the legend, or changing axis labels. To adjust properties for a visualization: Exploring Your Content 3-7

Undoing and Redoing Visualization Edits 1. In the active visualization toolbar, click Actions, and then select Properties to display the Properties dialog. 2. On the General tab, select the options to specify title formatting and enable and position the legend for the visualization. 3. In the dialog, click the Axis tab. 4. On the Axis tab, select which the options to affect the axis label titles and the start and end values for the axes. 5. In the dialog, click the Values tab. 6. On the Values tab, specify the appropriate options to specify how you want values handled in the visualization. Field Aggregation Method Number Format Description Specifies the method for aggregating data in the visualization, such as Auto, Sum, or Average. Specifies number formatting in the visualization, such as Auto, Percent, or Currency. 7. In the dialog, click the Analytics tab. 8. On the Analytics tab, click Add and then select Add Reference Line to set reference lines and bands that display at minimum or maximum values of a measure included in the visualization. 9. In the dialog, click the Edge Labels tab. 10. On the Edge Labels tab, expand a data element in the visualization, and set Show Total to On to display row or column totals in the visualization or Off to hide them. Undoing and Redoing Visualization Edits You can quickly undo an action and then redo the action if you change your mind. For example, you could try a different visualization type when you don t like the one you have just selected, or you can go back to where you were before a drill. These options are especially useful as you experiment with different visualizations. Use the Undo Last Edits or Redo Last Edits buttons on the project toolbar to undo and redo visualization edits. 3-8 Using Oracle Business Intelligence Cloud Service

Reversing Visualization Edits Note: You can also use Ctrl+Z to undo an edit and Ctrl+Y to redo it. Reversing Visualization Edits You can easily back out of the edits you make in a project. For example, if you move data elements to different drop targets in a visualization, and you decide you don t like those changes, you can easily reverse your changes. To reverse any edits you made in a project since you last saved it, click Actions on the project toolbar and then select Revert. Refreshing Visualization Content If you know that there is a newer set of data available for exploration in a project, you can refresh the data source data. This action clears the data cache and reruns queries to retrieve the latest data from the data sources to display in the canvas. To refresh the data displayed in a project, click Actions on the project toolbar and then select Refresh Data. Exploring Data Using Filters This topic describes how you explore your content using filters in Visual Analyzer. Topics: About Filters About Filter Types About Automatically Applied Filters Creating Filters Applying Range Filters Applying List Filters Applying Date Filters Building Expression Filters About Filters Filters help you understand your visualizations by reducing the amount of data that you are working with and by telling you what data you are looking at. In Visual Analyzer, filters determine the data set for all the visualizations in the canvas. When you have multiple filters in the filter bar, you can re-order them by dragging them to different placements. Exploring Your Content 3-9

Exploring Data Using Filters If visualizations are connected with a master-detail relationship, then you can click data in the master visualization to filter the detail visualization. Note: The filters in the filter bar at the top of the canvas filter all visualizations in the canvas. If you turn off Synchronize Visualizations, then a filter bar is added above each visualization. This smaller filter bar applies only to that visualization. For more information, see Specifying How Visualizations Interact with One Another. About Filter Types You can apply filters of various types including Range, List, Date, and Expression. Visual Analyzer assigns different types of filters automatically based on the type of data you are filtering. Here are the filter types you can use to explore content: Range filters are applied to data elements that are measures. Range filters limit data to a range of contiguous values, such as revenue of $100,000 to $500,000. Use histogram sliders for range filters to interactively adjust the range so as to understand how it relates to the value s distribution. For more information, see Applying Range Filters. List filters are applied to all data elements that are dimensions, except for those of type Date. List filters limits data when you want to select discrete members of data elements. See Applying List Filters. Date filters use calendar controls to adjust time or date selections. You select a single contiguous range of dates. For more information, see Applying Date Filters. Expression filters enable you to set advanced filtering across multiple data elements. For more information, see Building Expression Filters. About Automatically Applied Filters The Auto-Apply option is set by default on list filters that you add. When Auto-Apply Filters is on (checked), the selections you make in the filters are applied directly as you are in the process of making them. When Auto-Apply Filters is off (unchecked), the selections you make in the filters are not applied to the canvas until after you click the Apply button in the bottom-right corner of the list filter panel. You can turn off Auto-Apply for list filters by hovering your mouse over the top right of the filter bar, clicking the Actions icon, and selecting Auto-Apply Filters. 3-10 Using Oracle Business Intelligence Cloud Service

Exploring Data Using Filters Creating Filters You can create filters yourself, and you can let Visual Analyzer apply filters automatically as a result of the actions that you take on visualizations, such as drilling. Here are some of the ways that you can add a filter to a project: From the Data Elements pane, drag a data element to the filter bar. From the Data Elements pane, right-click a data element and select Create Filter. From the Explore pane, drag a data element to the filter bar. Optionally, add an expression filter as described in Building Expression Filters. Note: For visualizations that are part of master-detail relationships, selected data in the master visualization applies a filter to all the other visualizations in the canvas. For more information on master-detail relationships and synchronizing visualizations, see Specifying How Visualizations Interact with One Another. Applying Range Filters Applying List Filters Once you add a range filter to a visualization, you then can change the selections it includes. To use a range filter: 1. In the filter bar, click the filter to view the Range list. 2. In the Range list, click By to view the Selections list. All members that are being filtered in the canvas have check marks next to their names. 3. Optionally, in the Selections list, for any selected member you want to remove from the list of selections, click the member. The check mark disappears next to the previously selected member you clicked. 4. Optionally, in the Selections list, for any non-selected member you want to add to the list of selections, click the member. The check mark appears next to the member you click. 5. Optionally, set the range you want to filter on by moving the sliders in the histogram. The default range is from minimum to maximum, but as you move the sliders, the Start field and End field adjust to the range you set. 6. Click off the filter to close the filter panel. Once you add a list filter to a visualization, you can change the selected members it includes. To use a list filter: Exploring Your Content 3-11

Exploring Data Using Filters Applying Date Filters 1. In the filter bar, click the filter to view the Selections list. 2. Optionally, to the left of the Selections list, use the Search field to find the members you want to add to the filter. 3. Scroll down the list of members (or through the Search results) and click once on a member to add it to the Selections list. 4. Optionally, add more members to the Selections list. 5. Optionally, in the Selections list, you can click a member to remove it from the list of selections, causing the member to be filtered out of the canvas. 6. Optionally, in the Selections list, you can click the eye icon next to a member to cause it to be filtered out of the canvas but not removed from the list of selections. 7. Optionally, click Add All or Remove All at the bottom of the filter panel to add or remove all members to or from the Selections list at once. 8. Click off the filter to close the filter panel. 9. Optionally, to clear the filter selections, right-click in the filter bar, and then select Clear Filter Selections. 10. Optionally, to remove the filter, right-click in the filter bar, and then select Remove Filter. Once you add a date filter to a visualization, you can change the selections it includes. To use a date filter: Building Expression Filters 1. In the filter bar, click the filter to view the Calendar Date list. 2. In the Start calendar, select the date that begins the range on which you want to filter. Use the Previous arrow and Next arrow to move backward or forward in time, or use the drop-down lists to change the month or year. 3. In the End calendar, select the date that ends the range on which you want to filter. 4. Optionally, to start over and select new dates, click the Action icon and then select Clear Filter Selections. 5. Click off the filter to close the filter panel. If you want a free-form filter, you can build an expression. An expression filter is a special type of filter that allows you to specify the filter in the form of an expression that may reference one or more data elements. You build expressions using Visual Analyzer s Expression Builder. You can drag and drop data elements, and then choose operators to apply. Visual Analyzer validates the expression for you before you apply it. To build an expression filter for an attribute or measure: 3-12 Using Oracle Business Intelligence Cloud Service

Exploring Data in Other Ways 1. In the filter bar, click the Action icon and select Add Expression Filter. 2. In the Expression Filter panel, compose an expression. For more information, see About Composing Expressions. 3. In the Label field, give the expression a name. 4. Optionally, click Validate to check whether the syntax is correct. 5. Fix any errors, if necessary. 6. Click Apply. The expression is applied to the visualizations on the canvas. 7. Click off the filter panel to view your results in the canvas. Another use of the Expression Builder is in creating calculations, but this is different from creating expression filters. If you want to create a calculation, see Creating Calculated Data Elements. Exploring Data in Other Ways While adding filters to visualizations helps you narrow your focus on certain aspects of your data, you can take a variety of other analytic actions to explore your data such as drilling, sorting, and selecting. When you take the analytic actions described in this topic, Visual Analyzer applies filters automatically for you. Here are some of the analytic actions that you can take when you right-click content in visualizations: Use Sort to sort attributes in a visualization, such as product names from A to Z. Use Drill to drill to a data element, and you can drill through hierarchies in data elements, such as drilling to weeks within a quarter. You can also drill asymmetrically using multiple data elements. For example, you can select two separate year members that are columns in a pivot table, and drill into those members to see the details. Use Drill to [Attribute Name] to directly drill to a specific attribute within a visualization. Use Keep Selected to keep only the selected members and remove all others from the visualization and its linked visualizations. For example, you can keep only the sales that are generated by a specific sales associate. Use Remove Selected to remove selected members from the visualization and its linked visualizations. For example, you can remove the Eastern and Western regions from the selection. Exploring Your Content 3-13

About Composing Expressions Use Add Reference Line or Band to add a reference line to highlight an important fact depicted in the visualization, such as a minimum or maximum value. For example, you might add a reference line across the visualization at the height of the maximum Revenue amount. You also you might add a reference band to more clearly depict where the minimum and maximum Revenue amounts fall on the Revenue axis. Note: To add a reference band to a visualization, right-click it and select Add Reference Line to display the Properties dialog. On the Analytics tab, in the Method field, toggle Line to Band. About Composing Expressions You can compose an expression to use in an expression filter or in a calculation. For both expression filters and calculations, you use the Expression Builder. Expressions that you create for expression filters must be boolean (that is, they must evaluate to true or false). Expressions that you create for calculations are not limited in this way. Note: While you compose expressions for both expression filters and calculations, the end result is different. A calculation is a new data element that you can create and then add to your visualization. An expression filter, on the other hand, is just another filter that you can apply to the data in your visualization. You can compose an expression in various ways: You can directly enter text and functions in the Expression Builder by typing. You can add data elements from the Data Elements pane (drag and drop, or double-click). You can add functions from the function panel (drag and drop, or double click). Creating Calculated Data Elements You can use the Add Calculation dialog to create a new data element typically a measure to add to your visualization. For example, you could create a new measure called Profit. This new data element might involve the Revenue and Discount Amount measures. To add a calculation: 1. Launch the Add Calculation dialog in one of two ways: At the bottom of the Data Elements shelf tab, click Add Calculation. Right-click the My Calculations folder and select Add Calculation. 2. In the Expression Builder, compose an expression. For more information, see About Composing Expressions. For example, to create the new measure called profit, compose this expression: "Sample Sales Lite"."Base Facts"."Revenue"-"Sample Sales Lite"."Base Facts"."Discount Amount" 3. Optionally, click Validate. 3-14 Using Oracle Business Intelligence Cloud Service

Specifying How Visualizations Interact with One Another Note: If you click Save without first clicking Validate, Visual Analyzer validates the expression, and if the expression is invalid, it keeps the dialog open. 4. In the Display field, enter a data element name. 5. Click Save. The new data element is now created and you can use it in your visualizations as you would any other data element. For example, in visualization drop targets or in filters. Specifying How Visualizations Interact with One Another You use the Synchronize Visualizations setting to specify how the visualizations on your canvas interact. By default, visualizations are linked for automatic synchronization. You can turn off Synchronize Visualizations to unlink your visualizations for automatic synchronization. When Synchronize Visualizations is on (checked): All filters and actions that produce filters (such as Drill, Keep Selected, Remove Selected) are applied to all visualizations in the canvas. For example, if you have a canvas with multiple visualizations and you drill in one of the visualizations, a corresponding filter is added to the filter bar and it affects all visualizations on the canvas. When Synchronize Visualizations is off (unchecked): The analytic actions like Drill or Keep Selected affect only the visualization to which you applied the action. In this mode, the filters are displayed in a small filter bar above each visualization. There is an additional option, Use as Master that is available from all visualizations context menu. If Use as Master is turned on for a given visualization, it becomes the master visualization for the canvas. This means that selecting data in the master applies a filter to all the other visualizations on the canvas. Exploring Your Content 3-15

Specifying How Visualizations Interact with One Another Note: There can be only one master (or none) per canvas. When a visualization is set as the master, a circled blue M displays before its name. 3-16 Using Oracle Business Intelligence Cloud Service

4 Adding Your Own Data This topic describes how to add your own data in Visual Analyzer. Video Tutorial Topics: Typical Workflow for Adding Data from External Sources About Adding Your Own Data About Characteristics for External Sources Adding Data from External Sources Blending Data that You Added Refreshing Data that You Added Updating Details of Data You Added Controlling Sharing of Data You Added Removing Data that You Added Deleting Data that You Added Typical Workflow for Adding Data from External Sources Here are the common tasks for adding data from external sources. Task Description More Information Add data Blend data Refresh data Control sharing of external sources Add data from external sources. Blend data from external sources with an existing subject area. Refresh data when you know the external source was updated. Specify which users can access the data that you added. Adding Data from External Sources Blending Data that You Added Refreshing Data that You Added Controlling Sharing of Data You Added Adding Your Own Data 4-1

About Adding Your Own Data Task Description More Information Remove data Remove data that you added. Removing Data that You Added About Adding Your Own Data You can easily add data from external sources. Adding your own data is sometimes referred to as mash-up. You can add data in these ways: Add your own data to analyze on its own. You can create a project that is based solely on data from an external source without adding that data to an existing data model on the server. Add your own data as an external subject area to connect with an existing subject area. Many organizations have warehouses full of data that is waiting to be modeled so that users can visualize that data. When you use Visual Analyzer, you can create a project with a subject area that has already been modeled on the server. You can then easily add diverse data sets from multiple sources without involving your Information Technologies department. As you add the data, Visual Analyzer loads and blends the external data to fit with the existing subject area. In your data analysis and discovery, you can experiment ad hoc without changing the data models on the server. For example, you can overlay metrics on enterprise data such as updating a progress report against the new budget that your manager shared with you. You can enrich visualizations of data with new attributes such as how a recent blizzard affected shipping times. You can define custom roll-ups and segments such as seeing how revenue segmentation changes if products are re-classified. Suppose that you have a subject area that contains data about sales, such as Products, Brands, and Salespeople. You have a spreadsheet file that contains Target Revenue sales figures, which do not exist in the subject area. You d like to create a visualization that combines Product and Brand values from the subject area with the Target Revenue figures from your spreadsheet. When you add the data, you match the Product and Brand columns from the spreadsheet with those in the subject area and add Target Revenue as a measure. The matching connects the spreadsheet with the subject area. When you drag the three columns to the canvas, Visual Analyzer selects the best visualization for that data, a horizontal stacked bar chart. 4-2 Using Oracle Business Intelligence Cloud Service

About Characteristics for External Sources When you add data to projects, you can blend operational, production, out-of-band, external, and non-data warehouse systems into the runtime reporting environment. In Visual Analyzer, data modelling is implied rather than explicit. The system does the work for you, but you can make manual adjustments if you want to. For more information, see Blending Data that You Added. When you blend external data files, the columns that you introduce behave as though they are part of the data model, even though you have not made any changes on the server. The data that you add is saved by name on the server. You can add the data to projects and share it with other users. You can delete the data from the server when you need to preserve space. For more information, see Deleting Data that You Added. About Characteristics for External Sources A data source that you add must have certain characteristics. The data must be from a Microsoft Excel spreadsheet file, with the XLSX extension (signifying a Microsoft Office Open XML Workbook file) and a maximum size of 1 MB. The files that you add are saved to your cloud system. Each user has a maximum allowed storage of 10 MB. All users in one organization have a maximum allowed combined storage of 100 MB. A data source either extends a dimension by adding attributes or extends facts by adding measures and optionally attributes. Hierarchies cannot be defined in external data sources. Various criteria apply to sources that extend a dimension by adding attributes: Matches can be made only to a single dimension. The set of values in match columns must be unique in the external data source. For example, if the data source matches on zip code, then zip codes in the external source must be unique. Adding Your Own Data 4-3

Adding Data from External Sources Matches can be between one or composite columns. An example of a one-column match is that product key matches product key. For composite columns, an example is that company matches company and business unit matches business unit. All other columns must be attributes. Various criteria apply to sources that add measures: Matches can be made to one or more dimensions. The set of values in match columns does not need to be unique in the external data source. For example, if the data source is a set of sales matched to date, customer, and product, then you can have multiple sales of a product to a customer on the same day. Matches can be between one or composite columns. An example of a one-column match is that product key matches product key. For composite columns, an example is that company matches company and business unit matches business unit. The data source that adds measures can include attributes. You can use these attributes only alongside the external measures and not alongside the curated measures in visualizations. For example when you add a source with the sales figures for a new business, you can match these new business sales to an existing time dimension and nothing else. The external data might include information about the products sold by this new business. You can show the sales for the existing business with those of the new business by time, but you can t show the old business revenue by new business products, nor new business revenue by old business products. You can show new business revenue by time and new business products. When you save a project or an analysis, permissions are synchronized between the project or analysis and the external sources that it uses. If you share the project or analysis with other users, then the external sources are also shared with those same users. Be aware of the effect of mixing columns that don t match from data sources with a subject area. For example, suppose that you have a subject area that includes a Product attribute and an Orders attribute. You create a pivot table that includes those two attributes with a Revenue measure from a data source. The data source that includes the Revenue measure includes a Product column that matches the Product attribute in the subject area, but the data sources does not include an Orders columns. No Revenue data is shown in the pivot table for the Orders attribute. Adding Data from External Sources You can introduce your own external sources directly into a production reporting environment without changing the data model. Visual Analyzer automatically conforms the external data to the curated enterprise data. You can add data to blend with an existing subject area or create a new project without a subject area that includes data from an external source. A project can contain one subject area with one or more external subject areas, or a project can contain one external subject area. Subject areas and external subject areas have separate, distinct icons in the Data Sources pane to help you identify them. For more information, see About Characteristics for External Sources. To add data from an external source: 4-4 Using Oracle Business Intelligence Cloud Service

Adding Data from External Sources 1. From the Home page in Oracle BI Cloud Service, click Create a Visual Analyzer Project. 2. In the Add Data Source dialog, select the Select a Subject Area tab. 3. Click the appropriate subject area, then OK. 4. In the left pane, click the Data Sources shelf tab. 5. Right-click the Data Sources pane, and select Add Data Source. You can also click the Add Data Source link at the bottom of the Data Sources pane or right-click anywhere in the pane to display the Add Data Source option. 6. In the Add Data Source dialog, select either the Select a Saved File tab (if the file is in saved storage) or the Upload a File tab (if the file is stored locally). Note: When you select to add a saved file and already have a subject area for the project, you see a list of those saved files that are already connected by default. You can select and add a source that is not connected. 7. Select the appropriate file and click OK. If you selected a saved file, then the external data source is added to the project and you can skip to the end of this procedure. 8. If the file contains multiple sheets, then select the sheet with the data to load and click OK. 9. When uploading a source for the first time, edit the values in the Source Name and Description fields to be more meaningful to you. Adding Your Own Data 4-5

Blending Data that You Added 10. Preview a sample of the columns and values from the external source. Visual Analyzer automatically matches columns in the external source with the appropriate items in the data model. Note how columns will be added as measures, as attributes, or matched with an existing column in the subject area. 11. To exclude a column from being added, hover over the column name and click the check mark. Note: A column that is unavailable and marked with a red information symbol is invalid and excluded from being added to the data source. You can hover over the symbol to learn the reason why the column is invalid. 12. Click OK to accept the data associations that have occurred automatically or see Blending Data that You Added for details on manually editing the associations. The data model expands to include the data from the source that you added. Note: You can load a new data set independently of an existing subject area, which means that you can analyze most any data in Visual Analyzer. From the project toolbar, select New, and then Project. In the Add Data Source dialog, select an existing file from saved storage or upload the file from a local disk. Blending Data that You Added You might have a project that includes data from a subject area and find that an external source includes data that enhances that subject area. You can blend the data from the external source with the subject area after adding the data to the project. For example, the external source might contain new dimensions that extend the attributes of the subject area or new facts that you can use alongside the measures that already exist in the subject area. When you add data from external sources, Visual Analyzer tries to find matches for the data that is added. Visual Analyzer automatically matches external dimensions where they share a common name and have a compatible data type with attributes in the subject area. You can also fine-tune the blending of the data from the external source into the subject area. To blend data that you added: 1. Add data as described in Adding Data from External Sources. 2. In the upper-right corner of the project s title bar, click Source Diagram. 4-6 Using Oracle Business Intelligence Cloud Service

Blending Data that You Added 3. Click the number along the line that connects the external source to the subject area to display the Connect Sources dialog. 4. In the Connect Sources dialog, make changes as necessary. a. To change the match for a column, click the name of each column to select a different column from the external data source or from the subject area. Note: If columns have the same name and same data type, then Visual Analyzer recognizes them as a possible match. You can customize this and specify that one column matches another by explicitly selecting it even its name is not the same. You can select only those columns with a matching data type. b. Click Add Another Match, then select a column from the external source and from the subject area to match. Adding Your Own Data 4-7

Refreshing Data that You Added c. For a measure that you are uploading for the first time, specify its aggregation type such as Sum or Average. See Specifying Aggregation for Measures in Fact Tables for descriptions of aggregation types. d. Click the X to delete a match. 5. Click OK to save the matches from the external source to the data model on the server. Refreshing Data that You Added After you add data, you might need to refresh the data from its source if you learn that it has changed. To refresh data that you previously added, you must ensure that the newer spreadsheet file contains a sheet with the same name as the original one. In addition, the sheet must contain the same columns that are already matched with the subject area. In Visual Analyzer, you can completely replace data that you previously added, if you add new data to the data source and rename that data source the same as the existing one. You are prompted to verify that you want to overwrite the existing data and it doesn t matter whether the sheet name or columns match. To refresh data that you added: 1. In the Data Sources pane of Visual Analyzer or the Subject Areas pane of Oracle BI Cloud Service, right-click the data that you want to refresh. 2. Select Reload Data. 3. In the dialog, select the source that contains the newer data and click Open. 4-8 Using Oracle Business Intelligence Cloud Service

Updating Details of Data You Added 4. Review the data to refresh and click OK. The original data is overwritten with new data, which is displayed in visualizations in the project or analysis, once the visualization is refreshed. Updating Details of Data You Added After adding data, you can inspect its properties and update details such as its description and aggregation. 1. In the Data Sources pane of Visual Analyzer, right-click the data and select Inspect. 2. Inspect the properties and update the description of the data as appropriate. 3. In the Columns area, specify whether to change a column to measure or attribute as appropriate. For measures, specify the aggregation type, such as Sum or Average. See Specifying Aggregation for Measures in Fact Tables for descriptions of aggregation types. 4. To specify if others can share the data, see Controlling Sharing of External Subject Areas. 5. Click OK to save your changes to the data model. Controlling Sharing of Data You Added After you add data, the data is visible only to you as the user who uploaded and owns it. You as the owner or other users with appropriate permissions can specify the data as a shared resource that other users who have access to the server environment can include immediately in projects. You control which users can share the external data. To control sharing of external data: 1. In the Data Sources pane, right-click the external data and select Inspect. 2. In the Permissions tab, double-click a user or role to grant access. Select the appropriate level of access: Full Control, Modify, Read, or No Access. Adding Your Own Data 4-9

Removing Data that You Added 3. In the Permissions tab, click the X beside a user or role to remove it from the selection of permissions that you are managing. Removing Data that You Added You can remove data that you have added from an external source. If you remove data, it is removed from the project or analysis. Removing data differs from deleting data, as described in Deleting Data that You Added. To remove data that you added: 1. In the Data Sources pane of Visual Analyzer or the Subject Areas pane of Oracle BI Cloud Service, right-click the data that you want to remove. 2. Select Remove from Project or Remove from Analysis to remove data from the list. Deleting Data that You Added You can delete data that you have added, when you need to free up space in cloud storage. Deleting permanently removes the external source from cloud storage. You can delete only external sources. You cannot delete subject areas that you have included in projects or analyses. Deleting data differs from removing data, as described in Removing Data that You Added. To delete data that you added: 1. In the Data Sources pane of Visual Analyzer or the Subject Areas pane of Oracle BI Cloud Service, right-click the data that you want to remove. 2. Select Delete to erase the data from cloud storage. 4-10 Using Oracle Business Intelligence Cloud Service

Part III Reporting Data in Oracle Business Intelligence Cloud Service This part explains how to work with reports of data in Oracle BI Cloud Service. Chapters: Creating Analyses Viewing Data in Different Ways Building Dashboards Filtering and Selecting Data for Analyses Prompting in Analyses and Dashboards Making Analyses Interactive Accessing and Organizing Catalog Content

5 Creating Analyses This topic describes how to create an analysis for Oracle BI Cloud Service. Topics: Typical Workflow for Creating Analyses Creating Your First Analysis Setting Properties for Columns Exporting Content from Analyses and Dashboards Editing Formulas or Calculated Measures Adding Data from External Sources to Analyses Blending Data that You Added to an Analysis Setting Properties for Analyses Setting Your Preferences Advanced Techniques: Importing Formatting from Another Analysis Advanced Techniques: Combining Columns to Display Data Differently Advanced Techniques: Examining the Logical SQL Statements for Analyses Advanced Techniques: Referencing Stored Values in Variables Typical Workflow for Creating Analyses Here are the common tasks to start creating analyses. Task Description More Information Create an analysis Set properties for columns Work with the data in the analysis. Select and arrange columns that you want to use in an analysis. Specify properties such as heading and value formats, display of data, and conditional formatting. Add formulas and calculated measures to the analysis. Creating Your First Analysis Setting Properties for Columns Editing Formulas or Calculated Measures Creating Analyses 5-1

Creating Your First Analysis Task Description More Information Affect the values of data in the analysis. Specify filters, selection steps, groups, and calculated items for the analysis. Filtering and Selecting Data for Analyses Creating Your First Analysis You can quickly create an analysis to query against your organization's data. The analysis results help you answer your business questions. For example, you can create an analysis using the SampleApp subject area Brand and Revenue columns. You then review the results of the analysis to answer key business questions about the revenue generated by product brand. Video Tutorial To quickly create an analysis: 1. On the Home page, click Create an Analysis. 2. Optionally in the Subject Areas pane, click Sort Subject Area, then select A to Z to sort in ascending order. Select Z to A to sort in descending order. Select Sort in Saved Order to return the list order to its original state. 3. Add the columns that you want to include in the analysis by dragging and dropping them from the Subject Areas pane to any position within the Selected Columns pane. 5-2 Using Oracle Business Intelligence Cloud Service

Creating Your First Analysis Tip: You can select multiple non-contiguous columns by using the Ctrl key, selecting each column to include, and then dragging the columns to the Selected Columns pane. 4. To change the column order, use the crosshairs on the column to drag and drop the column to a different position. 5. To remove the column, use the Selected Columns pane, click Options beside the column name, and then click Delete. To remove all columns, click Remove all columns from criteria. Note that there is no undo action available for this option. Tip: Instead of removing columns, you can hide the columns whose appearance adds no value to the analysis. For information, see Setting Properties for Columns. 6. Click the Results tab to see the results of the analysis in a table or pivot table. 7. Click Save Analysis to display the dialog to save the analysis. 8. In the Save As dialog, select a folder and specify a name and optional description for the analysis. If you want others to be able to view the analysis, then save it in a folder under the Company Shared folder. If you don t want anyone else but yourself to be able to view the analysis, then save it in My Folders. 9. Click Refresh Display at the bottom of the pane to double-check that the analysis is listed under the folder in which you saved it. Creating Analyses 5-3

Setting Properties for Columns Setting Properties for Columns When you build an analysis, you can edit column properties to control the look and feel of the column. For example, you can specify that values in the Revenue column are displayed with two decimal places and a dollar sign. To set column properties: 1. Open the analysis for editing. 2. In the Selected Columns pane, click Options beside the column name to display the Column Properties dialog. 3. Specify how you want column values to be displayed. For more information, see Applying Formatting to Content. 4. Format column headings and custom text, and add data display conditions. For more information, see Formatting Columns. 5. Specify what action you want to happen when a user clicks a column heading or value. For more information, see Adding Interactivity to Analyses. 6. Set default column formatting. For more information, see Setting Default Formats for Your System. 7. Click OK. Applying Formatting to Content You can apply basic formatting to values in many types of content including columns, views, and dashboard page sections. For example, you might want region names in a column to be displayed as Arial 14 point and red. You might also want state names to be displayed as Calibri 12 point and blue. To apply formatting to content: 1. Open the analysis and open a column for format editing. The Column Properties dialog, Style tab is displayed. 2. Specify the style characteristics of the column such as font, cell alignment, and border. 5-4 Using Oracle Business Intelligence Cloud Service

Setting Properties for Columns 3. Optionally save the formatting for this column as the system wide default format. For more information, see Setting Default Formats for Your System. 4. Optionally, at the top of the dialog, click Clear Cell Format to remove the specifications that you have made and to return the settings to the values that they had when defaults were last saved. To format multiple objects in the same way, click Copy Cell Format, and then paste the formatting to the appropriate place. 5. Click OK. Formatting Columns When you create an analysis, you can edit properties for columns to control their appearance and layout. You can also specify formatting to apply only if the contents of the column meet certain conditions. For example, you can specify that values that exceed $1 million in the Revenue column are displayed with a green background. To apply formatting to a column: 1. Open the analysis and then open the column for format editing. 2. In the Column Properties dialog, click the Column Format tab. 3. To hide the column in the analyses without affecting value aggregation, select the Hide check box. For example, you might want to build an analysis that includes only Illinois customers. You can hide the Customers.State column because you only added this column for filtering purposes and its appearance adds no value to the analysis. 4. To enter your own values in the Folder Heading and Column Heading fields, select the Custom Headings check box. You can use these fields to reference variables and format the heading values. These values identify the column in the analysis. For more information, see Advanced Techniques: Referencing Stored Values in Variables. Creating Analyses 5-5

Setting Properties for Columns 5. To affect the display of repeating data values for the column, select one of the Value Suppression options. When the same value occurs in multiple consecutive rows, you can specify to show that value only once. When you do this, it can make it easier to see the relationships in the data. For example, suppose that one column lists customer names and another column lists the regions that those customers are in. The region data could be repeated for each customer row. If you specify to not display repeated values, then the distinctions in that data can be more apparent. 6. To override the default display of data for the column, click the Data Format tab. The options on the tab differ depending on the data type. For the text data type, the tab includes the Treat Text As and Custom Text Format fields. From the Treat Text As list, you can select to display the values as plain text, HTML, or a link. Based on your choice, the "Custom Text Format" field displays the applicable HTML string used to display the data. If you select Custom Text Format, then you can write HTML calls that provide formatting. You can also enter any valid HTML string, including JavaScript, VBScript, and so on. The first character must be the at sign (@). This character enables devices that are incapable of displaying the custom format to display the data in the appropriate default format. For example, the following sample HTML code sets the width and height of a column in tables and pivot tables. In the example, the text html enclosed in brackets ([html]) means to use HTML. The at sign character represents the dynamic contents of the column. @[html]<span style="width:200px; height:50px>@</span> 7. To specify if column values are displayed in a certain way based on certain criteria, click the Conditional Format tab. Conditional formats can include colors, fonts, images, and so on, for the data and for the cell that contains the data. 8. Click Add Condition, and then select a column. The New Condition dialog is displayed. 9. Select an operator such as is equal to / is in or is greater than. 10. Specify a value for the operator by either entering a value directly (such as 1000000) or by selecting a value from the list. 11. Optionally, click Add More Options to add a variable to the condition. For information, see Advanced Techniques: Referencing Stored Values in Variables. 12. Specify the formatting to apply when the condition is true, as described in Applying Formatting to Content. 13. Click OK. 5-6 Using Oracle Business Intelligence Cloud Service

Setting Properties for Columns Making Your Analyses Dynamic You can specify what you want to happen when a user clicks a column heading or value in an analysis. For example, you could specify that when a user clicks the Product column value, it drills down into the data that was summed to create the column value. Video Topics: Adding Interactivity to Analyses Making Interactions Available Adding Interactivity to Analyses In analyses, views that display data are not static. You can make views dynamic by specifying the interactions that are available to those who left-click in a view or rightclick to display a popup menu. The default primary interaction is a left-click that drills down to detail in the data, if data is hierarchical. Other interactions are available as options on a right-click popup menu. These interactions can include displaying a web page and linking views such that one view drives changes to data in one or more other views. You can also specify that no interactions are available. For example, you can specify the default primary interaction (the left-click action) for the Region column as Drill. This enables you to drill down to information by state by left-clicking in the column. To add interactivity to an analysis: 1. Open the analysis and then open the column for format editing. 2. In the Column Properties dialog, click the Interaction tab. The default primary interaction for column headings and values in views is Drill, which enables users to drill down to more detailed information. 3. Optionally select an interaction from the drop-down menu in the Column Heading section. 4. Optionally select a primary interaction from the menu in the Value section. Creating Analyses 5-7

Setting Properties for Columns Interaction Action More information None Drill (Default) Action Links Send Master-Detail Events 5. Click OK. Disables all interactions on the column. Displays a deeper level of detailed content if the data is hierarchical. If no hierarchy is configured for the column, then drilling is not enabled. Opens a web page or navigates to supporting BI content. Links views so that one view drives changes in one or more other views. None Drilling in Results Adding Actions to Analyses Linking Views in Master- Detail Relationships You can specify the interactions that are available at runtime when you right-click a dashboard column or data cell. Here s an example of the available interactions when you right-click a product name in the Products column. This column is in a Top Product Performers Based on Revenue table. Of the selections shown, you can set Drill, Create Group, and Create Calculated Item. Making Interactions Available When you add interactions to analyses, you then make those interactions available to others in popup menus. To make analyses interactions available to others: 1. Open the analysis for editing. 2. Click either the Analysis editor: Criteria tab or Analysis editor: Results tab. 5-8 Using Oracle Business Intelligence Cloud Service

Setting Properties for Columns 3. Click Edit Analysis Properties on the toolbar. 4. Click the Interactions tab of the Analysis Properties dialog. 5. Select the appropriate interactions from the list. 6. Click OK. Setting Default Formats for Your System If you have the appropriate privileges, then you can save the formatting of a column as default formatting. When you set a system-wide default, it can provide users with a more consistent experience and save them time when working with analyses. For example, suppose that your organization decided to use Arial as the font family for all text columns in all analyses. Suppose that a decision is later made to switch to Times New Roman for all text columns. You can simply save Times New Roman as the system-wide default for text columns. All existing analyses that contain text columns in which the font family is specified as Default (Arial) are updated automatically. You specify a specific value, such as Arial, only when you are certain that you want that value rather than the system default value. A best practice is to change the default value rather than overriding the default with specific values. To set default column formatting: 1. Open the analysis and open the column that you want to format for editing. 2. In the Column Properties dialog, select an option to create the column formatting. Option Restore column property defaults Save as the system-wide default for this column Save as the system-wide default for this data type Purpose Returns the property values for the column back to the last saved default values. Save the properties as the system-wide default for this column in all analyses in which it is used. Save the properties as the system-wide default for all columns that have the same data type as this column. Creating Analyses 5-9

Exporting Content from Analyses and Dashboards Note: You cannot save and restore the settings on the Column Properties dialog, Conditional Format tab. You can change a column format option if the value is set to Default (System). The column acquires whatever is currently set as the system default value. 3. Click OK. Exporting Content from Analyses and Dashboards You can export content from analyses and dashboards. Topics: Exporting the Results of Analyses Exporting Dashboards and Dashboard Pages Tips for Exporting Exporting the Results of Analyses You can export analyses results to various formats, including Microsoft Office Excel and Adobe PDF. For example, you can export a Stock Control analysis, so that one of your suppliers can see the results in Microsoft Excel. To export the results of an analysis: 1. Open the analysis for editing. 2. Click Export this Analysis. 3. Select the export option that you want, such as export to a PDF file, an Excel spreadsheet, or a Powerpoint presentation. Select Data to export data as a commaseparated or tab-delimited list of values in a file. You can then open the file in an application such as Excel. Select Web Archive to export as an MHT file that you can display in a browser. You can also export an analysis from a dashboard page by clicking Export below the analysis. The Export link is available only if the dashboard designer included the link. Exporting Dashboards and Dashboard Pages You can export an entire dashboard or a single dashboard page to Microsoft Excel 2007+. When you export dashboard content to Microsoft Excel, the state of the dashboard (such as prompts or drills) won t change. For example, you can export the dashboard page that contains the Brand Revenue analysis. This enables brand managers to review this data in Microsoft Excel. To export a dashboard or a dashboard page: 1. Open the dashboard or dashboard page that you want to export. 2. On the Dashboard page toolbar, click Page Options, select Export to Excel, and select either Export Current Page or Export Entire Dashboard. 5-10 Using Oracle Business Intelligence Cloud Service

Editing Formulas or Calculated Measures Tips for Exporting If you export an entire dashboard: Each page is included on its own sheet in an Excel workbook. Each sheet is given the name of its corresponding dashboard page. 3. Use the File Download dialog to open or save the dashboard or dashboard page as a spreadsheet file. Here are some tips to keep in mind as you export analyses, dashboards, and dashboard pages. By default, the Value Suppression option in the "Column Properties dialog: Column Format tab" determines if the cells in tables or pivot tables that span rows and cells that span columns are repeated when exporting to Excel (rather than always repeated). Do not suppress values when exporting to Excel if those who use the Excel spreadsheets want to manipulate the data. If Value Suppression is set to Suppress, then cells that span rows and cells that span columns are not repeated. For example, in a table that has Year and Month values, Year is displayed only once for Month values. This value suppression is useful if you want to simply view data in Excel spreadsheets. If Value Suppression is set to Repeat, then cells that span rows and cells that span columns are repeated. For example, in a table that has Year and Month values, Year is repeated for all Month values. By default, when you export to PDF, rows are split across page breaks rather than kept together. You can export as many as 65,000 rows of data from an analysis in a Comma Separated Values (CSV) file format. You can export as many as 1,000 rows of data into a file formatted with Microsoft Excel (.xlsx) format. Action links are not included in exported formats, for example, Excel and PDF. Data values (that is, numbers and dates) are exported in raw format with full number precision and format mask, rather than as a string in the data format specified, when exporting to Excel. While you can export directly to an Excel format, you might notice better performance during the export of large numbers of rows if you export first to CSV, and then import that file into Excel. Editing Formulas or Calculated Measures You can fine-tune the columns in an analysis by editing the formulas of columns or editing calculated measures. Topics: Editing the Formula for a Column Editing Calculated Measures Creating Analyses 5-11

Editing Formulas or Calculated Measures Editing the Formula for a Column You can edit the formulas for attribute columns and measure columns when you specify the criteria for an analysis. This editing affects the column only in the context of the analysis and does not modify the formula of the original column in the subject area. Video A column formula specifies what the column values represent. In its most basic form, such as "Revenue Metrics"."Revenue", a column takes the data from the data source as is. You can edit the formula to add functions, conditional expressions, and so on. This editing enables you to present analysis results in a variety of ways. For example, you can edit the formula of a Revenue column to display values after a 10% increase in revenue. You can do this by writing a formula that multiplies the Revenue column by 1.1. To edit the formula for a column: 1. Open the analysis for editing. 2. In the Selected Columns pane, click Options beside the column name. 3. Select Edit Formula. 4. On the Column Formula tab of the Edit Column Formula dialog, enter a formula in the Column Formula pane. By default, the name of the column on the Selected Columns pane is displayed in the Column Formula pane. You can use the operator and character buttons on the bottom of the Column Formula pane to help build the formula. 5-12 Using Oracle Business Intelligence Cloud Service

Editing Formulas or Calculated Measures You can use the f(...) button to display the Insert Function dialog that enables you to include a function in the column formula. For example, you can build a formula based on a SQL function, such as RANK("Sales Measures"."Dollars"). For information about SQL functions, see Expression Editor Reference. You can use the Filter... button to display the Insert Filter dialog that enables you to include a filter expression in the column formula. Start the filter expression with at least one measure column. Include a Boolean expression that contains no measure columns or nested queries. For example, you can build a formula that uses the SQL FILTER function to filter the data, such as FILTER("Sales Measures"."Dollars" USING ("Markets"."Region" = 'EASTERN REGION'). You can use the Variable button to include a variable in the formula. For information, see Advanced Techniques: Referencing Stored Values in Variables. You can reference a column name in the formula using the form Folder- Name.Column.Name. If either the folder name or the column name includes nonalphanumeric characters (such as spaces or underscores), then enclose each name in double quotes. You can enclose the names in double quotes even if they have all alphanumeric characters. You use single quotes to include literals or constants that have a data type of string. For example, you can include constants such as John Doe or Best Selling Product in a formula. 5. Optionally, in the Subject Areas pane, double-click a column to replace the column name in the Column Formula pane. This action creates a new formula. 6. Optionally, click the Bins tab to perform "binning," which enables you to combine values for the column into sets. For example, suppose that the Region column has a value EASTERN. You can specify "My Home Region" instead as the text that displays for that value in a view. Binning differs from groups in that groups enable the view to display each member in the group. Click Add Bin to display the dialog for creating a filter expression to display as a CASE statement in the column's formula. You can combine multiple values or ranges of values from a given column into bins. When you add and name the bins, all instances of the various values that comprise the bin in the result set values are replaced by the bin name. Aggregations are performed accordingly as well. For example, you can specify that all values over $10M are displayed as "My10M."]] Note: The Bins tab is not affected by the button bar in the Formula area in the Formula tab. However, if you create a CASE statement using the Bins tab, the button bar is hidden when you click the Column Formula tab. You must clear all bins to display the button bar. 7. Click OK. On the Analysis editor: Results tab, the column displays its values with the formula applied. Creating Analyses 5-13

Adding Data from External Sources to Analyses Editing Calculated Measures You can use calculated measures that are derived from other measures and created by using formulas. For example, you might need to find the value after discounts are taken off the revenue. You create a calculated measure that subtracts the Discounted Amount from the Revenue value. To create a calculated measure for an analysis: 1. Open the analysis for editing. 2. On the Analysis editor: Results tab, click New Calculated Measure on the toolbar to display the dialog. 3. Edit the formula for the calculated measure as described in Editing the Formula for a Column. 4. Click OK. Adding Data from External Sources to Analyses You can introduce your own external sources directly into a production reporting environment without having to change the data model. Oracle BI Cloud Service 5-14 Using Oracle Business Intelligence Cloud Service

Adding Data from External Sources to Analyses automatically conforms the external data to the curated enterprise data. Adding your own data is sometimes referred to as mash-up. You can add data into an existing subject area or create a new analysis without a subject area that includes data from an external source. An analysis can contain no subject areas and one external subject area, or one subject area with multiple external subject areas. Subject areas and external subject areas have separate, distinct icons in the Criteria tab of the Analysis editor to help you identify them. For more information, see About Characteristics for External Sources To add data from an external source to an existing analysis: 1. Open the analysis for editing. 2. In the Criteria tab, click Add Data Source. 3. In the dialog, select the file that contains the data to add and click Open. 4. If the file contains multiple sheets, then select the sheet with the data to load and click OK. 5. Edit the values in the Data Source Name and Description fields to be more meaningful to you. 6. Select whether to add columns that add measures to facts or that extend dimensions by adding attributes. 7. Preview a sample of the columns and values from the external source. Oracle BI Cloud Service automatically matches columns from the external source with the appropriate items in the data model. Note how columns will be added as measures, as attributes, or matched with an existing column in the subject area. 8. To exclude a column from being added, deselect the box beside the column name. Note: A column that is unavailable and marked with a red information symbol is invalid and excluded from being added to the data source. You can hover over the symbol to learn the reason why the column is invalid. 9. Click Load to accept the data associations that have occurred automatically or see Blending Data that You Added to an Analysis for details on manually editing the associations. Note: To create an analysis that uses only data from an external source, on the Home page, click New, then Analysis, and Add Data Source. Select the data to include. After adding data, you perform various tasks: Blending Data that You Added to an Analysis Refreshing Data that You Added Removing Data that You Added Deleting Data that You Added Creating Analyses 5-15

Blending Data from External Sources to Analyses Blending Data from External Sources to Analyses You might have an analysis that includes data from a subject area and find that an external source includes data that enhances that subject area. You can blend the data from the external source with the subject area. For example, the external source might contain new dimensions that extend the attributes of the subject area or new facts that you can use alongside the measures that already exist in the subject area. When you add data from external sources, Oracle BI Cloud Service tries to find matches for the data that is added. Oracle BI Cloud Service automatically matches external dimensions where they share a common name and have a compatible data type with attributes in the subject area. You can also fine-tune the blending of the data from the external source into the subject area. To blend data that you added to an analysis: 1. Add data as described in Adding Data from External Sources to Analyses. 2. In the Subject Areas pane of Oracle BI Cloud Service, right-click the data and select Inspect. 3. For each column, select either Match with, Add Measure, or Add Attribute. For matches, select the column in the subject area to match. For a measure that you are uploading for the first time, specify its aggregation type such as Sum or Average. See Specifying Aggregation for Measures in Fact Tables for descriptions of aggregation types. Note: If columns have the same name and same data type, then Oracle BI Cloud Service recognizes them as a possible match. You can customize this and specify that one column matches another by explicitly selecting it even its name is not the same. You can select only those columns with a matching data type. 4. To exclude a column from being added, deselect the box beside the column name. 5. Click Update to confirm your changes. Setting Properties for Analyses You can set analysis properties to specify how results are displayed and how data is handled. You can also set which actions are available when users right-click in a pivot table, table, treemap, or trellis view. For example, you can create a custom message for the Brand Revenue analysis. This message could display when a filter on the Revenue column is too restrictive and no results are displayed. To set properties for an analysis: 1. Open the analysis for editing. 2. In the Criteria tab toolbar or the Results tab toolbar, select Edit Analysis Properties to display the Analysis Properties dialog. 5-16 Using Oracle Business Intelligence Cloud Service

Setting Properties for Analyses 3. On the Results Display tab, select options to affect the display of results. For example, select No Results Settings to specify the default or custom message that display if no results are returned when you run the analysis. You might see the message, for example, if you have a very restrictive filter placed on the columns in the analysis. You do not see the custom message if you simply create the analysis without including columns. 4. In the dialog, click the Interactions tab. 5. Specify which actions (for example, Drill) are available when you right-click in a pivot table, table, graph, treemap, or trellis view. 6. In the dialog, click the Data tab. 7. On the Data tab, specify the appropriate options to specify how you want the data handled in the analysis. Field Include Null Values Display of Columns Added in Criteria Tab Description Specifies if null values are displayed in the analysis when the entire row or column contains all nulls. If you select this checkbox, null suppression is turned off for all views. This suppression applies to the entire edge (that is, the row and column axis) of the analysis. Specifies how columns are added to an analysis from the Criteria tab after displaying the analysis results: Display in existing and new views Exclude from existing views, but display in new views 8. Click OK. Creating Analyses 5-17

Setting Your Preferences Setting Your Preferences While working with Oracle BI Cloud Service, you can set account preferences to reflect where you live and to support how you work. For example, you might select a specific Sales Dashboard as your starting page and Pacific Standard Time as your time zone. By specifying a starting page, you can get to Oracle BI Cloud Service and start working with your dashboard right away. To set preferences: 1. In the global header, click Signed In As username and select My Account. 2. Use the tabs of the My Account dialog to specify preferences, such as your starting page, locale, and time zone. 3. Click OK to save your changes. Advanced Techniques: Importing Formatting from Another Analysis You can import formatting from a saved analysis and its views to format new or existing analyses. Most people don t need to perform this task. For example, suppose that you have applied different colors to the Store, City, and Product columns of the Last Year's Brand Revenue analysis. You can import formatting from that analysis to apply colors to the This Year's Brand Revenue-2013 analysis. You apply formatting by using the Import Formatting button from two toolbars: Location Compound Layout toolbar View editor toolbar Application Applies formatting to all applicable views in the layout. Applies formatting only to the view that you are editing. The following table describes the views from which you can import formatting: View Type Narrative Pivot table, table, and trellis Static text Title View Selector Action Imports only the text font color. Imports formatting for the columns, green bar specifications, sub-totals and grand totals, and section properties. Imports only the text font color. Imports formatting for the title, logo, subtitle, start time, and help URL. Imports only the caption formatting. Formatting is applied slightly differently depending on whether you import formatting applied to columns, views, or view containers in the Compound Layout. References: About Applying Formatting from Columns 5-18 Using Oracle Business Intelligence Cloud Service

Advanced Techniques: Importing Formatting from Another Analysis About Applying Formatting from Views About Applying Formatting from Containers Importing Formatting from a Saved Analysis to a Target Analysis About Applying Formatting from Columns Applying formatting from columns works best for views when the saved analysis has the same number of columns as the target column. For a single column, formatting is applied to all columns in the tables, pivot tables, and trellises of the target analysis. For multiple columns, formatting is applied from left to right for column headings and values. Suppose the number of columns in the target analysis is greater than the number in the saved analysis. Then, the closest column's format is repeated in the subsequent columns. For example, suppose that the saved analysis contains four columns formatted with the following colors in this order: red, green, blue, and yellow. In the target analysis, its six columns would acquire these colors in the following order: red, green, blue, yellow, yellow, yellow. About Applying Formatting from Views Formatting is applied to a view only if a view of that type exists in the target analysis. The imported formatting applies to all views of that type in the target analysis. For example, suppose that a saved analysis contains a table with custom formatting. If you import that formatting into a target analysis that contains three tables, then all three tables inherit that formatting. About Applying Formatting from Containers In the Compound Layout, you can specify formatting properties such as background color, borders, and padding to view containers. Suppose you import that container formatting. The views in the target analysis inherit the exact container formatting properties as the views in the saved analysis. The layout of the views in the two analyses are not required to be exactly the same. If the target analysis contains more views than the source analysis, then extra views inherit the imported formatting. For example, suppose that a saved analysis contains two tables that are stacked on top of each other in the Compound Layout. Suppose that the target analysis contains four tables that are laid out two by two. The source analysis has only one layout column of two table views. The two tables in each of the first and second layout columns of the target analysis inherit the applied formatting. Importing Formatting from a Saved Analysis to a Target Analysis You can import formatting from one analysis to another. For example, suppose you have an analysis that contains one column. You have applied formatting to that Revenue column such as font family, horizontal alignment, and background color. You can save the analysis and use it as a template. You can apply it to the same formatting to all columns in a view in another analysis. To use a saved analysis to modify the appearance of another analysis: Creating Analyses 5-19

Advanced Techniques: Combining Columns to Display Data Differently 1. Open the analysis for editing. 2. Display the target analysis in the Analysis editor: Results tab, or edit the view. 3. Click Import formatting from another analysis on the toolbar. 4. In the Select Analysis dialog, navigate to the saved analysis. 5. Click OK. Advanced Techniques: Combining Columns to Display Data Differently You can combine columns based on set operations such as Union or Intersect. By combining columns, you create a column for displaying the data in a different way. Most people don t need to perform this task. For example, you can combine a Region column with a City column and create a column named Regions and Cities. The analysis must meet certain criteria if you want to use set operations: The number and data types of the columns must be the same. You cannot use hierarchical columns, selection steps, or groups when you combine criteria. To combine columns based on set operations: 1. Open the analysis for editing. 2. On the Analysis Editor: Criteria tab, in the Selected Columns pane toolbar, click Combine results based on union, intersection, and difference operations. The Set Operations area is displayed in the Selected Columns pane. Note the boxes with the dotted line borders. These boxes indicate the kind of column that you must combine with those that you have previously included in the analysis. 3. In the Subject Areas pane, select the columns to combine with the original columns. Note that the dotted line borders and contents have been replaced. 4. In the Result Columns area on the Set Operations pane, click on the Union button and select a set operation. The following table describes the operations. Operation Union Union All Intersect Minus Description Specifies that only nonduplicate rows from all columns are returned. Specifies that rows from all columns, including duplicate rows, are returned. Specifies that only rows common to all columns are returned. Specifies that only rows from the first column that are not in the second column are returned. 5-20 Using Oracle Business Intelligence Cloud Service

Advanced Techniques: Examining the Logical SQL Statements for Analyses 5. Click the Result Columns link. The Selected Columns pane shows the newly combined columns. 6. To rename the heading of the column: a. Click the Options button for the column. b. Select Column Properties. c. Select Column Format. d. Ensure that Custom Headings is selected. e. In the Column Heading box, enter the new heading. f. Click OK. 7. Click the Results tab to view the columns in a table view. Advanced Techniques: Examining the Logical SQL Statements for Analyses You can examine the logical SQL to see the XML code and logical SQL statement that is generated for an analysis. You can optionally create an analysis based on that SQL statement using the Advanced tab of the Analysis editor. Most people don t need to perform this task. Before using the Advanced tab, keep in mind that this tab is only for advanced users and developers who have the appropriate responsibilities to access the Advanced tab. You must understand advanced SQL statements and have expertise working with the metadata for analyses. You must also understand the content and structure of the underlying data sources. To examine the SQL statement that is generated for an analysis: 1. Open the analysis for editing. 2. Click the Analysis editor: Advanced tab. 3. Use the read-only box in the SQL Issued area to examine and copy the SQL statement that is used for executing the analysis. 4. Click New Analysis to create an analysis based on the SQL code. Advanced Techniques: Referencing Stored Values in Variables You can reference stored values in variables in several areas of Oracle BI Cloud Service, including in analyses, dashboards, and actions. Most people don t need to perform this task. For example, suppose that you wanted to create an analysis whose title displays the current user's name. You can do this by referencing a variable. You can use fives types of variables: session, repository, presentation, request, and global. Topics: About Session Variables About Repository Variables Creating Analyses 5-21

Advanced Techniques: Referencing Stored Values in Variables About Session Variables About Presentation Variables About Request Variables About Global Variables Creating Global Variables Syntax for Referencing Variables For information about using variables when modeling data, see Creating Variables to Use in Expressions. A session variable is a variable that is initialized at login time for each user. When a user begins a session, Oracle BI Cloud Service creates a new instance of a session variable and initializes it. There are as many instances of a session variable as there are active sessions on Oracle BI Cloud Service. Each instance of a session variable can be initialized to a different value. There are two types of session variables. Type System Non-system Description A session variable used by Oracle BI Cloud Service for specific purposes. System session variables have reserved names that cannot be used for other kinds of variables (such as static or dynamic repository variables and non-system session variables). A system variable that the administrator creates and names. For example, the administrator might create a SalesRegion non-system variable that initializes the name of a user's sales region. The administrator creates non-system variables using Data Modeler. For information, see Creating Variables to Use in Expressions. About Repository Variables A repository variable is a variable that has a single value at any point in time. A static repository variable has values that persist and do not change until the administrator changes it. A dynamic repository variable has values that are refreshed by data returned from queries. About Presentation Variables A presentation variable is a variable that you can create as part of the process of creating a column prompt or a variable prompt. Type Column prompt Description A presentation variable created as part of a column prompt is associated with a column, and the values that it can take come from the column values. To create a presentation variable as part of a column prompt, in the New Prompt dialog, you must select Presentation Variable in the Set a variable field. Enter a name for the variable in the Variable Name field. For information on working with column prompts, see Creating Column Prompts. 5-22 Using Oracle Business Intelligence Cloud Service

Advanced Techniques: Referencing Stored Values in Variables Type Variable prompt Description A presentation variable created as part of a variable prompt is not associated with any column, and you define the values that it can take. To create a presentation variable as part of a variable prompt, in the New Prompt dialog, you must select Presentation Variable in the Prompt for field. Enter a name for the variable in the Variable Name field. For information on working with variable prompts, see Creating Variable Prompts. About Request Variables The value of a presentation variable is populated by the column or variable prompt with which it was created. That is, each time a user selects one or more values in the column or variable prompt, the value of the presentation variable is set to the value or values that the user selects. A request variable enables you to override the value of a session variable but only for the duration of a database request initiated from a column prompt. You can create a request variable as part of the process of creating a column prompt. You can create a request variable as part of the process of creating one of the following types of dashboard prompts: A request variable that is created as part of a column prompt is associated with a column, and the values that it can take come from the column values. To create a request variable as part of a column prompt, in the New Prompt dialog, you must select Request Variable in the Set a variable field. Enter the name of the session variable to override in the Variable Name field. A request variable that is created as part of a variable prompt is not associated with any column, and you define the values that it can take. To create a request variable as part of a variable prompt, in the New Prompt dialog (or Edit Prompt dialog), you must select Request Variable in the Prompt for field. Then enter a name of the session variable that you want to override in the Variable Name field. The value of a request variable is populated by the column prompt with which it was created. That is, each time a user selects a value in the column prompt, the value of the request variable is set to the value that the user selects. The value, however, is in effect only from the time the user presses the Go button for the prompt until the analysis results are returned to the dashboard. Certain system session variables (such as, USERGUID or ROLES) cannot be overridden by request variables. Other system session variables, such as DATA_TZ and DATA_DISPLAY_TZ (Timezone), can be overridden if configured in the Oracle BI Administration Tool. Note: Only string and numeric request variables support multiple values. All other data types pass only the first value. Creating Analyses 5-23

Advanced Techniques: Referencing Stored Values in Variables About Global Variables Creating Global Variables A global variable is a column created by combining a specific data type with a value. The value can be a Date, Date and Time, Number, Text, and Time. The global variable is evaluated at the time the analysis is executed, and the value of the global variable is substituted appropriately. Only users with the BIAdvancedContentAuthor role can manage (add, edit, and delete) global variables. You create a global value during the process of creating an analysis by using the Edit Column Formula dialog. The global variable is then saved in the catalog and made available to all other analyses within a specific tenant system. You can save a calculation as a global variable then reuse it in different analyses. By simply creating a global variable, you do not have to create a new column in the Data Modeler. To create a global variable: 1. Open the analysis for editing. 2. In the Selected Columns pane, click Options beside the column name. 3. Select Edit Formula to display the Column Formula tab. You can create a custom header for the global variable by using this tab. 4. Click Variable and select Global to display the Insert Global Variable dialog. 5. Click Add New Global Variable to display the New Global Variable dialog. 5-24 Using Oracle Business Intelligence Cloud Service

Advanced Techniques: Referencing Stored Values in Variables 6. Enter the value for the Name. For example, gv_region, date_and_time_global_variable, or rev_eastern_region_calc_gv. See Syntax for Referencing Variables for syntax requirements. Note: The name for a global variable must be fully qualified when referencing the variable, and therefore is prefixed by the text "global.variables". For example, a global variable set to calculate revenue is displayed in the Column Formula dialog as follows: "Base Facts"."1- Revenue"*@{global.variables.gv_qualified} 7. Enter values for the Type and Value. Note: If you are selecting "Date and Time" as the data type, then enter the value as in the following example: 03/25/2004 12:00:00 AM If you are entering an expression or a calculation as a value, then you must use the Text data type, as in the following example: "Base Facts"."1- Revenue"*3.1415 8. Click OK. The new global variable is added to the Insert Global Variable dialog. 9. Select the new global variable that you just created, and click OK. The Edit Column Formula dialog is displayed with the global variable inserted in the Column Formula pane. The Custom Headings check box is automatically selected. 10. Enter a new name for the column to which you have assigned a global variable to more accurately reflect the variable. 11. Click OK. Syntax for Referencing Variables You can reference variables in analyses and dashboards. How you reference a variable depends on the task that you are performing. For tasks where you are presented with fields in a dialog, you must specify only the type and name of the variable (not the full syntax), for example, referencing a variable in a filter definition. For other tasks, such as referencing a variable in a title view, you specify the variable syntax. The syntax that you use depends on the type of variable as described in the following table. Creating Analyses 5-25

Advanced Techniques: Referencing Stored Values in Variables Type Syntax Example Session Repository Presentation or request Global @{biserver.variables['nq_session.var iablename']} where variablename is the name of the session variable, for example DISPLAYNAME. @{biserver.variables.variablename} or @{biserver.variables['variablename']} where variablename is the name of the repository variable, for example, prime_begin @{variables.variablename}[format] {defaultvalue} or @{scope.variables['variablename']} where: variablename is the name of the presentation or request variable, for example, MyFavoriteRegion. (optional) format is a format mask dependent on the data type of the variable, for example #,##0, MM/DD/YY hh:mm:ss. (Note that the format is not applied to the default value.) (optional) defaultvalue is a constant or variable reference indicating a value to be used if the variable referenced by variablename is not populated. scope identifies the qualifiers for the variable. You must specify the scope when a variable is used at multiple levels (analyses, dashboard pages, and dashboards) and you want to access a specific value. (If you do not specify the scope, then the order of precedence is analyses, dashboard pages, and dashboards.) Note: When using a dashboard prompt with a presentation variable that can have multiple values, the syntax differs depending on the column type. Multiple values are formatted into comma-separated values and therefore, any format clause is applied to each value before being joined by commas. @{global.variables.variablename} where variablename is the name of the global variable, for example, gv_region. When referencing a global variable, you must use the fully @{biserver.variables['nq_se SSION.USER']} @{biserver.variables.prime_b egin} or @{biserver.variables['prime_ begin']} @{variables.myfavoriteregio n}{eastern REGION} or @{MyFavoriteRegion} or @{dashboard.variables['myfa voriteregion']} or (@{mynumvar}[#,##0]{1000}) or (@{variables.myowntimesta mp}[yy-mm-dd hh:mm:ss]{) or (@{mytextvar}{a, B, C}) @{global.variables.gv_date_n _time} 5-26 Using Oracle Business Intelligence Cloud Service

Advanced Techniques: Referencing Stored Values in Variables Type Syntax Example qualified name as indicated in the example. Note: The naming convention for global variables must conform to EMCA Scripting language specifications for JavaScript. The name must not exceed 200 characters, nor contain embedded spaces, reserved words, and special characters. If you are unfamiliar with JavaScripting language requirements, consult a third party reference You can also reference variables in expressions. The guidelines for referencing variables in expressions are described in the following sections. Session Variables The guidelines for referencing session variables in expressions are: Include the session variable as an argument of the VALUEOF function. Enclose the variable name in double quotes. Precede the session variable by NQ_SESSION and a period. Enclose both the NQ_SESSION portion and the session variable name in parentheses. For example: "Market"."Region"=VALUEOF(NQ_SESSION."SalesRegion") Presentation Variables When referencing a presentation variable, use this syntax: @{variablename}{defaultvalue} where variablename is the name of the presentation variable and defaultvalue (optional) is a constant or variable reference indicating a value to be used if the variable referenced by variablename is not populated. To type-cast (that is, convert) the variable to a string, enclose the entire syntax in single quotes, for example: '@{user.displayname}' If the @ sign is not followed by a {, then it is treated as an @ sign. When using a presentation variable that can have multiple values, the syntax differs depending on the column type. Use the following syntax in SQL for the specified column type in order to generate valid SQL statements: Text (@{variablename}['@']{'defaultvalue'}) Numeric (@{variablename}{defaultvalue}) Creating Analyses 5-27

Advanced Techniques: Referencing Stored Values in Variables Date-time (@{variablename}{timestamp 'defaultvalue'}) Date (only the date) (@{variablename}{date 'defaultvalue'}) Time (only the time) (@{variablename}{time 'defaultvalue'}) For example: "Market"."Region"=VALUEOF(NQ_SESSION."SalesRegion") Repository Variables The guidelines for referencing repository variables in expressions are: Include the repository variable as an argument of the VALUEOF function. Enclose the variable name in double quotes. Refer to a static repository variable by name. Refer to a dynamic repository variable by its fully qualified name. For example: CASE WHEN "Hour" >= VALUEOF("prime_begin") AND "Hour" < VALUEOF("prime_end") THEN 'Prime Time' WHEN... ELSE...END 5-28 Using Oracle Business Intelligence Cloud Service

6 Viewing Data in Different Ways You can view data in different ways by adding views to analyses. Topics: Typical Workflow for Viewing Data in Different Ways About Views Adding Views Editing Views Editing Various Types of Views Graphing Data in Analyses Saving Views Rearranging Views Refreshing the Results in Views Printing Views Changing Print Options for Views Previewing How Views Are Displayed on Dashboards Removing Views Sorting Values in Views Clearing Sorts in Views Drilling in Results Resizing Rows and Columns in Views Suppressing Null Values in Views Assembling Views for Display Linking Views in Master-Detail Relationships Modifying the Layout of Data in Views About Drop Targets in the Layout Pane Viewing Data in Different Ways 6-1

Typical Workflow for Viewing Data in Different Ways Typical Workflow for Viewing Data in Different Ways Here are the common tasks to start adding views to analyses to view data in different ways. Task Description More Information Create an analysis Add a view Edit a view Remove a view Select and arrange columns that you want to use in an analysis. Add views to an analysis to visualize data in different ways. Use the editor that is available for each type of view to edit that view. Delete a view from a compound layout or from an analysis. Creating Your First Analysis Adding Views Editing Views Removing Views Save a view Save a view by saving the analysis. Saving Views Print a view Print a single view or group of views in printable HTML or printable PDF. Printing Views About Views A view is a visualization that helps communicate an outcome. Views enable you to look at results of analyses in meaningful, intuitive ways. Views give you different ways of looking at your data to help you discover patterns, trends, outliers, and other interesting characteristics of your data. You can add a variety of views to the results, such as graphs and pivot tables that allow drilling down to more detailed information, explanatory text, a list of filters that were used to limit the results, and more. For example, you can include a bar graph view of revenue. Adding Views By default when you create an analysis, you see either a table or pivot table view, depending on the columns that you selected. You can add other views to the analysis to enable you to visualize the data in different ways. For example, you can analyze trends for your Sales Forecast analysis by creating a new view and selecting Recommended Visualization and the Analyzing Trends option. 6-2 Using Oracle Business Intelligence Cloud Service

Editing Views Video To add a view: 1. Open the analysis for editing. 2. On the Results tab, click New View, then select one of the following options. The view is added the current compound layout. Option Best Visualization Recommended Visualization for View Type Description Oracle BI Cloud Service automatically creates the most appropriate view based on the data in the analysis. Select the kind of analysis that you want to perform and Oracle BI Cloud Service recommends the best views for that purpose and your data. For example, select Analyzing Trends or Comparing Explicit Results. You select the desired view type, such as Pivot Table or Gauge. 3. To format the container for the views in the analysis, click Format Container. 4. Complete the fields in the Format Container dialog to specify options such as alignment, colors, and borders. 5. Click OK. 6. Click Save Analysis. Editing Views Each type of view has its own editor. The editors include both common functionality across views and view-specific functionality. For example, you can edit a graph in a Brand Revenue analysis in the Graph editor to show the legend. The following procedure provides general information on editing views. For more information, see Editing Various Types of Views and Graphing Data in Analyses. To edit a view: 1. Open the analysis for editing. 2. Click the Analysis editor: Results tab. 3. To edit the view, click Edit View. 4. In the view editor (such as the Graph editor) make the appropriate edits, such as showing the legend. Viewing Data in Different Ways 6-3

Editing Various Types of Views 5. To affect the display of data in the view, see Modifying the Layout of Data in Views. You can perform tasks such as dragging and dropping columns. 6. Associate data views such that one view drives changes in one or more other views. For information, see Linking Views in Master-Detail Relationships. 7. Drag and drop named groups and named calculated items from the Catalog pane to the view. For information, see Manipulating Members Using Groups and Calculated Items. 8. To customize the selection of data in the view, see Refining Selections of Data. 9. Click Done. 10. To save the view, see Saving Views. Editing Various Types of Views This topic identifies additional information for editing various types of views. Topics: Editing Table and Pivot Table Views Editing Gauge Views Editing Performance Tile Views Editing Trellis Views Editing Treemap Views Editing Narrative Views About Editing Non-Data Views 6-4 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views Editing Table and Pivot Table Views Two common views for analyzing and displaying data are the table and pivot table. For example, you can edit a pivot table in the analysis and place Brand on the row edge to display its corresponding Revenue data for each Quarter and Region. You can include a table and a pivot table side-by-side in a compound layout. To edit a table or pivot table view: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Click View Properties to edit properties. You can set properties such as the following ones: The method to be used to browse data either scrolling or paging controls. The display of headings for the columns and the view. Formatting preferences such as size and colors. Green bar styling. Setting this property shows alternating rows or columns in a light green color, which is the default color that you can change. 4. Click OK to dismiss the dialog. Viewing Data in Different Ways 6-5

Editing Various Types of Views Editing Gauge Views 5. Click Edit View to display the Table View editor. 6. For a pivot table view, click the Graph Pivoted Results button on the toolbar to display the results of the pivot table in a graph view, which is displayed alongside the pivot table. The two views are fully linked, which means that changes made to one view are automatically reflected in the other. 7. Click Done. 8. To specify sorting in the view, see Sorting Values in Views. 9. To drill in the data in the view, see Drilling in Results. You can use gauge views to graphically compare performance to goals. Due to their compact size, gauges can be more effective than graphs for showing a single data value. Results show as dial, bar, or bulb gauges. For example, you can use a gauge to see whether Actual Revenue falls within predefined limits for a brand. The following figure shows a dial gauge: The following figure shows a bar gauge: The following figure shows a bulb gauge: To edit a gauge view: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 6-6 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views 3. Click View Properties to perform tasks such as the following: Specify the number of rows of gauges to display and placement of labels in Gauges per Row. Change the width and height of gauges and the appearance of titles and labels. Specify the scale of gauge limits and tick marks. For example, you can specify a custom gauge limit. You can specify a static value such as 1000 as either an actual value or as a percentage. The value that you specify depends on the range of data points. You must ensure that the maximum gauge limit is more than the maximum data point. Do so to ensure that all data points are displayed on the gauge. Specify the marker type for a dial gauge, such as Needle, Line or Fill. 4. Click OK to dismiss the dialog. 5. Click Edit View to display the Gauge View editor. 6. Click the Gauge Type button on the toolbar to select the type of gauge, such as bulb or dial. 7. Define thresholds for the gauge, as described in Setting Thresholds. 8. Click Done. Setting Thresholds You can set thresholds for display in gauges and funnel graphs. Each threshold has a high and a low value and is associated with a color in which the range identified by the threshold is displayed in the gauge, such as green for acceptable, yellow for warning, and red for critical. To set thresholds: 1. Click Edit View to display the view editor. 2. In the Settings pane, select either High values are desirable or Low values are desirable. For example, selecting High values are desirable lists the statuses in order from the most desirable indicator (such as Excellent) at the top to the least desirable indicator (such as Warning) at the bottom. Generally with columns such as Revenue, high values are desirable. With columns such as Expenses, low values are desirable. 3. In the Threshold list, specify the data values that highlight a particular range of values. The values must be between the minimum and maximum values set for the view's limits. The range that a threshold identifies is filled with a color that differs from the color of other ranges. To specify a data value, you can enter a static value directly in a Threshold field, or you can click Threshold Options to set the value based on a measure column, a variable expression, or the results of a SQL query. Select Dynamic to enable the system to determine the threshold value. Viewing Data in Different Ways 6-7

Editing Various Types of Views 4. Enter the labels for the ranges in the Status area. Editing Performance Tile Views Select Threshold Values to use the current threshold values as the label for the range. Select Specify Label to use text that you specify as the label for the range, such as Excellent. Performance tile views focus on a single piece of aggregate of data. By default, the first measure in the analysis on the Criteria tab is selected as the performance tile measure. You must set up aggregation and filters on the Criteria tab to ensure that the correct measure value is displayed in the tile. To change this measure, edit the performance tile view. To include additional performance tile views for each measure in an analysis, add a separate view for each measure. For example, you might want to edit a performance tile view to use Revenue as the measure. You can specify that the values and labels utilize the available space. The following figure shows performance tiles on a dashboard page: To edit a performance tile view: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Click View Properties to edit properties. You can set the following kinds of properties: Related to the size of the tile. That control the appearance of the tile, such as the background and border colors. You can apply conditional formatting to the tile. That abbreviate the value on the tile. A performance tile can show a value using its measure's default formatting or the value can be abbreviated to the nearest thousand, million, and so on. Examples of formatting are shown in the following table: Default Formatting Abbreviated Value 123,456.50 123K 123,456,789.50 123M 123,456,789,123.50 123B 4. Click one of the following buttons to align the performance tile label: 6-8 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views Button Fixed positions Utilize available space Description Sets (or "fixes") the positions of the labels. The label text is displayed in fixed positions. This option is recommended for layouts with multiple performance tiles (of the same size) in a row, where you want to ensure visual consistency by rendering text anchored at the same height despite variations in content. Evenly spaces the label text on the performance tile vertically. The label text utilizes all available space on the performance tile. Note that when you have multiple tiles placed beside each other, the labels might be displayed at different heights and look uneven based on the varying label content. 5. Click OK to dismiss the dialog. 6. Click Edit View to display the Performance Tile editor. 7. In the Styles pane, change the tile size to Small, Medium, or Large. Editing Trellis Views 8. Select a themed (or stylized) tile located below the Tile Size option buttons to change the theme for the performance tile. 9. Click Done. A trellis view is a type of graph view that displays a grid of multiple graphs, one in each data cell. A trellis view can be simple or advanced. A simple trellis displays a core inner graph multiplied across row sets and column sets, rendering many small multiples that are ideal for comparing and contrasting. An advanced trellis displays a grid of small spark graphs that are ideal for monitoring trends and spotting patterns in a data set. For more information, see About Simple Trellis Versus Advanced Trellis. The following figure shows a simple trellis view: Viewing Data in Different Ways 6-9

Editing Various Types of Views The trellis view, also referred to as a trellis graph, is the same as a pivot table with one major exception: the data cells within the trellis contain graphs. Whereas a standalone graph type such as a single bar graph or a single scatter graph works on its own, the trellis graph works only by displaying a grid of nested graphs, known as inner graphs. So a bar-graph trellis view is actually comprised of multiple bar graphs. To edit a trellis view: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Click View Properties to edit properties. You can set the following kinds of properties: Related to the grid canvas, such as legend location (simple trellis views only). Related to graph size for the visualizations that are included in the trellis. That specify the method to be used to browse data either scrolling or paging controls. That control the appearance of the trellis's grid and its visualizations, such as various style choices and the way that legends are displayed. That control the type of scale and the appearance of scale markers for each of the trellis's visualizations (simple trellis views only). That control the display of titles and labels (simple trellis views only). 4. Click OK to dismiss the dialog. 5. Click Edit View to display the Trellis editor. 6. In the Layout pane: 6-10 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views a. Drag and drop columns into the Columns and Rows fields to specify how data is arranged in the trellis. b. Select the type of graph you want to display for each of the cells in the trellis. c. Drag and drop columns to indicate how to color the graphs. 7. To specify sorting in the view, see Sorting Values in Views. 8. Click Done. About the Functions of Trellis Views For the most part, a trellis view behaves like a pivot table. The main difference between a trellis and a pivot table is the way the data cells are displayed. In the row and column label cells of a trellis, you can: Right-click to hide or move measure labels. Right-click to sort data. Drag to reposition rows and columns. In the data cells of a trellis, you can hover the mouse pointer to display related contextual information. Numeric data cells in a trellis behave the same as numeric data cells in a pivot table. The ways in which the behavior of a trellis view differs from the behavior of a pivot table are the following: Graph data cells There is no right-click functionality for the data cells in simple trellises, nor drilling in trellis graph data cells (left-click functionality). Microchart data cells When you hover the cursor over the data cells in spark graphs, you are shown contextual information (such as first, last, minimum, and maximum values) that otherwise is not displayed as it is in a pivot table view. About Simple Trellis Versus Advanced Trellis A trellis view has one of two types: Simple Trellis and Advanced Trellis. The Simple Trellis displays a single type of inner visualization, for example, all bar graphs. The inner visualization always uses a common axis, so that all inner graphs are viewed on the same scale. Having a common axis makes all graph markers easy to compare across rows and columns. This figure shows a simple trellis view: Viewing Data in Different Ways 6-11

Editing Various Types of Views The Advanced Trellis accommodates the display of multiple visualization types within its grid. An advanced trellis that illustrates sales trends might show a grid that contains numbers in the cells of one column (revenue, for example). Another column alongside the numbers column displays Spark Line graphs in its cells. Next to that column, a different microchart might be displayed, such as a column of Spark Bar graphs that visualize a different measure, such as unit totals. This figure shows an advanced trellis view: Each measure that is visualized is assigned a different inner graph type. Each cell of the grid is scaled independently. Think of an advanced trellis as a pivot table with spark graphs inside its data cells. But, for each measure that you add, you can optionally associate a dimension and render it as a microchart visualization. This makes an advanced trellis very different from a simple trellis. In a simple trellis, all of the measures are rendered in the same visualization, along with additional dimensions. 6-12 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views Design Considerations for Trellis Views and Microcharts This concept provides ideas to be considered when designing content displayed in trellis views. For all trellis views: For comparisons, select the Simple Trellis. For trend analysis, select the Advanced Trellis. Make the inner graphs that comprise a trellis readable and not too dense. A trellis view is not especially useful for displaying multiple series or multiple groups. If you cannot easily target a data point with the mouse (to display a tooltip), then the inner graph is likely too dense to be readable. For the Simple Trellis: Designing a simple trellis is like designing a pivot table, except that the total number of cells that can be rendered is much less for a trellis. The main difference between designing a simple trellis and designing a pivot table is that for a trellis, one or two of the dimensions can be associated with the visualization. You add many fewer dimensions to the outer edge. Design the trellis with a small number of outer-edge dimensions. The entire graph series should be visible at once (for easy comparison of like to like) with no need to scroll. If you must show additional dimensionality, then consider adding the dimensions to the graph prompt. When determining which data to show in column headers and which to show in row headers, ensure that the column headers show one or two dimensions (each dimension with a small number of members). For the Advanced Trellis: A common use case for an advanced trellis is to show trend graphs alongside numeric values, in a compressed form. So a typical advanced trellis contains a combination of spark graphs alongside number representations of the same measure. Ideally, include no dimensions in the column headers. Include the measure in the column headers. The dimensionality typically associated with a spark graph is time. Because a spark graph includes no visible labels, it is important that the data visualized is intrinsically ordered. For example, a spark graph that visualizes regions is meaningless, because the ordering of the regions (which would be the specific bars, in a Spark Bar graph) is not intuitive. Just as when designing pivot tables, you generally display time on the horizontal axis, with the other dimensions displayed on the vertical axis. The eye then scans from left to right to see how the dimensionality changes over time. Hierarchical columns do not work well with the Simple Trellis. When a hierarchical column is displayed on the outer edge, parents and children (such as Year and Quarter) are shown by default using a common axis scale. However, because Year Viewing Data in Different Ways 6-13

Editing Various Types of Views Editing Treemap Views and Quarter have different magnitudes, the markers in child graphs might be extremely small and hard to read against the parent scale. (Hierarchical columns do work well with the Advanced Trellis, because each data cell is a different scale.) Treemaps organize hierarchical data by grouping the data into rectangles (known as tiles). Treemaps display tiles based on the size of one measure and the color of the second measure. The following figure shows an example of a treemap view. The country names are grouped by region and area. This treemap shows the correlation of revenue for a country (based on average order size) across different regions for an area. By default, the first measure of the analysis in the Criteria tab is selected as the Size By measure, and the second measure is selected as the Color By measure. If there is only one measure in the analysis, this measure is the default for both Size By and Color By options. Additionally, the Style element defaults to Percentile Binning with "quartile" as the value for the number of bins. Treemaps have the following characteristics: Tiles are colored by percentile bins or continuously. First Group By dimension is displayed as the group (header) label. The order of the Group By dimensions implies the nesting order within the treemap. The last dimension in the Group By is the lowest level and this dimension name is displayed as the tile label. If the label is too long to fit on the tile, then it is truncated. Full values for the labels display in the tooltip. To edit a treemap view: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Click Edit Properties. You can set properties such as the following ones: The size of the treemap. Whether a legend is to be displayed to show the continuous color variations or binning for the treemap tiles. 6-14 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views The background color and fill of the legend. The border colors of the groups and tiles. 4. Click OK to dismiss the dialog. 5. Click Edit View to display the treemap view editor. 6. In the Layout pane, select the Percentile Binning or Continuous Color Fill options to change the color palette of the view. Style Percentile Binning Continuous Color Fill Description Specify that the color of the tiles within the treemap is displayed as a percentile bin. In the Bins list, select the number of bins to display in the treemap. You can select an integer, Quartile (4), or Decile (10). Values range from 2 to 12. The number of bins selected corresponds to the number of colors in the treemap. For example: You create a treemap for Region and Area. You specify Revenue as the Size By measure and Avg Order Size as the Color By measure. Then, you select Percentile Binning as the Style with 4 (Quartile) bins. The First Quartile represents those areas within the region that are under performing for the average order size by revenue. The Binning Properties area displays the percentage for the bin based on a total of 100% and is calculated based on the number of bins selected. Each percentage is color-coded and corresponds to the Color selection. Specify that the tiles within the treemap are displayed as a gradient color scheme. The low value gradient color is the minimum value for the selected Color By measure. The high value gradient color is the maximum value for the selected Color By measure. 7. Change the measures and attribute and hierarchal (excluding skip-level) columns to visualize the new data in more meaningful ways by using Group By, Size By, and Color By options. 8. Click Done. Editing Narrative Views A narrative view displays data results as one or more paragraphs of text. You use a narrative view to provide information such as context, explanatory text, or extended descriptions along with column values. You can perform various tasks in the narrative view editor: Type a sentence with placeholders for each column in the results. Specify how rows are separated. Apply cosmetic formatting to the fonts used in the narrative view, or import the font formatting from a previously saved view. Add references to variables. To edit a narrative view: Viewing Data in Different Ways 6-15

Editing Various Types of Views 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Click Edit View to display the narrative view editor. 4. In the Prefix field, enter the header for the narrative. This text is displayed at the beginning of the narrative. 5. In the Narrative box, enter the narrative text that is displayed for each row in the results. You can include both text and column values. Include a line break code at the end of this field to force each line of text and values onto its own line. To include column values, use an at sign (@), optionally followed by a number. Use an at sign by itself to indicate the first column. If you include multiple at signs, then the first occurrence of the sign corresponds to the first column, the second occurrence corresponds to the second column, and so on. Use @n to include the results from the designated column in the narrative. For example, @1 inserts the results from the first column in the analysis, and @3 inserts the results of the third column. For example, for an analysis that returns the region name in the second column, specify @2 to include the following values in the view: East Region and West Region. 6. In the Row separator field, enter a row separator for each line from the Narrative field that contains values. For example you might enter a string of plus signs (+) between each line. 7. In the Rows to display field, enter the number of rows from the column to return. For example, enter 5 to display values from the first 5 rows of the column. For a hierarchical column, you can use selection steps to display hierarchy levels with the hierarchical column. For example, create a step to select members based on hierarchy and add members of the specified level. A hierarchy level is considered a row. 8. In the Postfix field, enter the footer for the narrative. Ensure that the narrative ends in a line break, or that the footer begins with a line break. 9. Click Done About Editing Non-Data Views You often edit views that display data, such as tables, graphs, and gauges. You can also edit views that do not contain data. You can include the following types of views in analyses and dashboards: About Column Selector Views About Filters Views About Selection Steps Views About Static Text Views 6-16 Using Oracle Business Intelligence Cloud Service

Editing Various Types of Views About Title Views About View Selector Views About Column Selector Views A column selector view is a set of drop-down lists that contain pre-selected columns. Users can dynamically select columns and change the data that is displayed in the views of the analysis. One drop-down list can be attached to each column in the analysis, and multiple columns can be attached to each drop-down list. Updates that you make in the column selector view affect all the data views in the analysis. You add columns to drop-down lists from the Subject Areas pane. When you add columns in this way, they are not added to the Criteria tab for the analysis. Instead, when you display the Criteria tab, you see that the column is now referred to as a "Column Group" with the default column for the list specified also. The default column is the one on which you created the drop-down list. About Filters Views A filters view displays the filters in effect for an analysis. Filters, like selection steps, allow you to constrain an analysis to obtain results that answer a particular question. Filters are applied before the query is aggregated. For information, see Creating Filters for Columns. About Selection Steps Views A selection steps view displays the selection steps in effect for the analysis. Selection steps, like filters, enable you to obtain results that answer particular questions. Selection steps are applied after the query is aggregated. You cannot modify selection steps from this view editor. To modify the selection steps, exit the Selection Steps editor and use the Selection Steps pane. For information, see Refining Selections of Data. About Static Text Views A static text view adds static text to be displayed with the analysis results. You can include variables in a static text view, as shown in the following example. For information, see Advanced Techniques: Referencing Stored Values in Variables. [u] Static Text View [/u][br/] Region: @{variables.myfavoriteregion} - Year: @{variables.myfavoriteyear}[br/] System Time: @{system.currenttime}[dddd,mmmm dd,yyyy][br/] Product Version: @{system.productversion}[br/] [br/] About Title Views A title view displays a title, a subtitle, a logo, and timestamps to the results. If you do not specify a title, then the name of the saved analysis is used as the title. For unsaved analyses, the Title text box is blank. You can reference variables in the text fields of the Title editor. About View Selector Views A view selector view enables users to select a specific view of the results from among the saved views for an analysis. When placed on a dashboard, the view selector is Viewing Data in Different Ways 6-17

Graphing Data in Analyses displayed as a list from which users can choose the view that they want to display below the selector. Generally, you include views in the view selector that are not being displayed in the Compound Layout view. For example, you might create a table, graph, gauge, and view selector view for an analysis, but include only the table and view selector view on the Compound Layout view. When the analysis is displayed on a dashboard page, users can select the graph or gauge view from the view selector view. Graphing Data in Analyses This topic identifies additional information for graphing data in analyses. Topics: Editing Graph Views Editing Graph Views Zooming and Scrolling in Graphs Formatting the Visual Appearance of Graphs Limiting Data Displayed in Graphs and Gauges You can use graphs of various types for analyzing and displaying data. For example, in the Brand Revenue analysis, you can edit a bar graph to compare the product revenue for three different regions. The following figure shows a bar graph view on a dashboard page: To edit a graph view: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Click View Properties to edit properties. You can set the following kinds of properties: Related to the graph canvas, such as legend location. 6-18 Using Oracle Business Intelligence Cloud Service

Graphing Data in Analyses That control the appearance of the graph, such as the style. For axis limits and tick marks. That control the display of titles and labels for the graph. 4. On the Scale tab of the properties dialog, select Click to edit Scale Markers to display the Scale Markers dialog. Define scale markers, which are accenting lines or shaded background ranges that mark key points, thresholds, ranges, and so on in a graph. The following table describes the two types of scale markers: Type Line Range Description A line that is drawn across the graph at a specified position on the scale A shaded background area that is displayed behind the graph. You can apply line or range scale markers on one or more axes depending on the type of graph. 5. Click OK to dismiss the dialog. 6. Click Edit View to display the Graph editor. 7. Use various toolbar buttons to affect the display of the graph, as described in the following table: Button Type Subtype Style Effect Description Includes bar, line, and pie. Includes vertical or horizontal, depending on the graph type. Available choices for style depend on the graph type. Either a 2D or 3D effect. 8. Define thresholds for a funnel graph, as described in Setting Thresholds. 9. To drill in data in the view, see Drilling in Results. 10. Click Done. Zooming and Scrolling in Graphs If zooming and scrolling has been enabled for a graph, then the graph includes a Zoom icon. The Zoom icon enables you to zoom in and out of a graph's plot area using its axes. After you zoom in on an axis, you can scroll the axis. Enable zooming and scrolling with the General tab of the Graph Properties dialog. For example, while viewing a graph in results of a Brand Revenue analysis, you can zoom in on the Product Type axis. Doing so enables you to scroll the axis and view more data by product type. To zoom and scroll in a graph, hover the mouse cursor over the graph to reveal the Zoom button and click Zoom. If only one axis is enabled, select Zoom In or Zoom Out. Viewing Data in Different Ways 6-19

Graphing Data in Analyses If both axes of the graph are enabled for zooming and scrolling: Select Horizontal Axis, then either Zoom In or Zoom Out. A zoom and scroll slider is displayed on the X axis. To unzoom the X axis, select Actual Size. Select Vertical Axis, then either Zoom In or Zoom Out. A zoom and scroll slider is displayed on the Y axis. To unzoom the Y axis, select Actual Size. To unzoom both the X and Y axes, select Actual Size. (Optional) To use other zoom features: Use Zoom to zoom in and out incrementally. Drag the scroll thumb on an axis to dynamically scroll the graph, revealing portions of the graph that are out of view. Click the scroll buttons on an axis to scroll left and right (on the X axis), or up and down (on the Y axis). Use the resize handles to zoom in and out on an axis. Formatting the Visual Appearance of Graphs You can format the visual appearance of graphs. Formatting the visual appearance is based on two settings: The position of the graph elements (such as lines or bars in a line-bar graph or slices in a pie graph). See Formatting Graphs Based on Position. Conditions applied to columns. See Formatting Graphs Based on Columns. 6-20 Using Oracle Business Intelligence Cloud Service

Graphing Data in Analyses Formatting Graphs Based on Position Positional formatting enables you to customize the appearance of a graph based on the position of graph elements; that is, the numeric sequence in which graph elements (for example, bars) are displayed in a group. A group is determined by the attribute columns that are displayed in the Group By drop target area. (For information on drop target areas, see About Drop Targets in the Layout Pane). You can format the visual appearance of a graph based on position in terms of its color, line width, and line symbols. You cannot use positional formatting with waterfall graphs. Formatting Graphs Based on Columns Conditional formatting enables you to customize the appearance of a graph based on conditions applied to columns. The formatting is applied to the column values that meet the condition. You can specify a color in which to display graph data based upon a specific column value, or range of column values that meet the condition specified for the column. For example: Conditionally changing the color of a graph based on specific column values. You want to create a bar graph to compare sales between two beverages, Lemonade and Cola. When creating a bar graph, you specify two conditions, one where the bar representing Lemonade sales is yellow and another where the bar representing Cola sales is blue. Conditionally changing the color of a graph based on a range of column values. A sales manager wants to create a bar graph to compare sales for all representatives across two sales bands. When creating a bar graph the sales manager specifies two conditions, one where the bar is red for all sales representatives with sales less than $250,000, and another where the bar is green for all sales representatives with sales greater than $250,000. To format the appearance of a graph: 1. Click Edit Graph Properties on the toolbar of the graph editor. 2. Click the Style tab of the Graph Properties dialog. 3. Click Style and Conditional Formatting. 4. Click the Style Formatting tab to format the appearance of a graph based on the position of the graph elements. To add a custom formatted position: a. Select the tab for the graph element (for example, bar) to which you want to add a custom formatted position. b. Click Add new position. A new position entry is displayed in the Custom Formatted Positions table. c. Specify the formatting. For example, to select the color to be applied to the position, click the down arrow next to the Color box to access the Color Selector dialog. (Note that the formatting options depend on the element.) Viewing Data in Different Ways 6-21

Graphing Data in Analyses Note: If you specify 0 for the width of a line, then the legend marker changes from the default line marker to symbol markers for the line and for other lines in the graph. For example, the symbol markers are shown as the legend markers for all the lines in the graph. 5. Click the Conditional Formatting tab to format the appearance of a graph based on a condition that is applied to columns. To add a condition to a column: a. Click Add Condition Format and select the column to which you want to apply a condition. b. Select the operator and enter a column value, or a range of column values for this condition. c. Click OK. d. To select the color to be applied to column values when the condition is met, click the down arrow next to the Color box to display the Color Selector dialog. 6. Click OK. Rules for Applying Conditional Formats in Graphs Follow these rules when building and using conditions in graphs. You can create conditions only from columns that are being used by the graph. When format conditions conflict with each other, conflicting conditions are prioritized in the following order: 1. Conditional formatting on attributes. 2. Conditional formatting on measures 3. Style formatting based on the positions of graph elements. When a user drills on a graph that has conditional formatting applied, the following rules apply: A conditional format based on measures is not carried to the next level. (It does not make sense to carry the conditional format to a different level; for example if, in a geographic hierarchy, from Region to City.) A conditional format based on attributes is carried to the next graph if it has not been drilled on. For example, if you had the conditional format "Lemonade = Blue" and only drill on years, then "Lemonade = Blue" stays in place. Conditional formatting is not supported on subtotals and totals for waterfall graphs. 6-22 Using Oracle Business Intelligence Cloud Service

Graphing Data in Analyses Graph Exceptions for Conditional Formatting on Columns This reference lists the graph exceptions that apply to conditional formatting based on columns. Graph Type Line Line-Bar Radar Time Series Line Pareto Exception Only symbol formatting is allowed for the line. Formatting is applied only to the bars, not to the Pareto line. Limiting Data Displayed in Graphs and Gauges You can limit the data that is shown in graphs or gauges using section sliders. A section slider displays members of one or more attribute or hierarchical columns as values on a rectangular bar. The slider also provides mechanisms to select a value for that column such as increase and decrease buttons. The play button sequentially moves through the slider values. Topics: Defining Section Sliders in Graphs and Gauges Using Section Sliders in Graphs and Gauges Defining Section Sliders in Graphs and Gauges You can define a section slider to limit the data that is shown in a graph or gauge. For example, you can limit the data that is shown in a graph to a specific quarter in the year 2013. To define a section slider: 1. Open the analysis for editing. 2. Click the Analysis Editor: Results tab. 3. Create the graph or gauge. 4. Click Edit View on the graph or gauge view. 5. In the Layout pane, drag columns to the Sections drop target. 6. Select Display as Slider. 7. Click Section properties. 8. Specify the maximum number of values to display in the section slider, and then click OK. 9. To close the editor, click Done. Viewing Data in Different Ways 6-23

Saving Views 10. To save the changes, click Save Analysis. Using Section Sliders in Graphs and Gauges This topic describes how to use a section slider in a graph or gauge. Move the slider thumb to the desired value. Click the decrease button to move the slider thumb to the left. Click the increase button to move the slider thumb to the right. To sequentially move the slider through all the values, click the play button. The play button changes to a pause button that enables you to stop on a particular value. The data in the graph or gauge is limited by the current value indicated by the slider thumb. Saving Views You can save a view that you are working with at any time. To save a view, you must save the new or existing analysis. For example, you can create a Brand Revenue analysis, edit its table view, and decide to save it for the first time. 1. To save a view, click Save Analysis or Save As in the toolbar of the Results tab in the Analysis editor. Rearranging Views You can rearrange a view within a compound layout to be alongside the boundary of another view or to the outer boundary of the compound layout (where the view is displayed across the length or breadth of the compound layout). For example, you can rearrange the views in the Brand Revenue analysis. You can arrange the bar graph of Projected Revenue to be displayed before the line graph of Actual Revenue. To rearrange a view: 1. Place the cursor just inside the top edge of the view that you want to rearrange. 2. Click and hold the left mouse button on the view. The view is displayed as a transparent, movable object. 3. Drag and drop the view to the position that you want. The view is displayed in a position marked by a blue bar (the drop target). 6-24 Using Oracle Business Intelligence Cloud Service

Refreshing the Results in Views Refreshing the Results in Views When you work with views that show results data, such as the table and pivot table, you can refresh the results of the current analysis. For example, you can add a filter in the Brand Revenue analysis. After doing so, you might want to see the effects of your change. To refresh results in a view: 1. On the toolbar of the Analysis Editor: Results tab, click Refresh the results of the current analysis. Viewing Data in Different Ways 6-25

Printing Views Printing Views You can print views using HTML or Adobe PDF (Portable Document Format). For example, you can display and print the Brand Revenue analysis in a new browser window by selecting the Printable HTML option. To print views: 1. Print one or more views. To print a single view, click Print this analysis on the toolbar of the view's editor. To print a group of views that displayed in the Compound Layout, click Print this analysis on the toolbar of the Analysis Editor: Results tab. 2. Select Printable HTML or Printable PDF. For HTML, a new browser window displays the view or views to print. From the File menu of the new browser window, select Print. For PDF, an Adobe Acrobat window displays the view or views to print. Select the options in the window to save or print the file. Changing Print Options for Views You can specify settings for printing dashboard pages and views. For example, when printing the Revenue Dashboard that contains many views sideby-side on each page, you can set the Orientation to Landscape. Note: The print selections that you specify apply to PDF output only. If you then print the PDF file on a local or network printer, then the print selections specified in the browser are in effect. For example, the selection for paper size for the browser is in effect. To change print options for views: 1. On the toolbar of the Analysis Editor: Results tab, click Print & Export Options. The Print & Export Options dialog is displayed. 6-26 Using Oracle Business Intelligence Cloud Service

Previewing How Views Are Displayed on Dashboards 2. Specify the appropriate options on the dialog. For example, specify the paper size and orientation and whether to include a header and footer. 3. Click OK. Previewing How Views Are Displayed on Dashboards You can preview views to see how they are displayed on a dashboard page. For example, you can select Show how results will look on a dashboard. Doing so previews how results from a group of views are displayed in a dashboard. To preview views: 1. If you want to preview a single view: On the toolbar of the view's editor. click Show how results will look on a dashboard. 2. If you want to preview a group of views that is displayed in the Compound Layout: On the toolbar of the Analysis Editor: Results tab, click the Show how results will look on a dashboard. The dashboard preview is displayed in a new window. Prompts are displayed and applied in the preview. Removing Views You can remove a view from a compound layout or analysis. For example, you might find that the trellis view is not the best way to show the results of the Brand Revenue analysis. You can remove that trellis view. To remove a view from a compound layout, click Remove View from Compound Layout on the view's toolbar. Removing a view from a compound layout does not remove it from the analysis. To remove a view from an analysis, select the view, then click Remove View from Analysis in the Views pane on the Results tab. Removing a view from an analysis removes it from the analysis and any compound layout to which it was added. Viewing Data in Different Ways 6-27

Sorting Values in Views Sorting Values in Views You can sort values in table, graph, pivot table, and trellis views. You can sort on members, measures, and rows (where you see sideways triangles). You cannot sort on page or section edges. You can use many options to sort in views. For example, when you sort a column, you can select from the following options: Sort Ascending Enables you to sort the values in the column by ascending order, as a first-level sort. For example, string values sort alphabetically A through Z, numbers sort lowest to highest, and dates sort earliest to latest. Sort Descending Enables you to sort the values in the column by descending order, as a first-level sort. Add Ascending Sort Specifies that an ascending sort for this column is added as another sort for the analysis. Add Descending Sort Specifies that a descending sort for this column is added as another sort for the analysis. Clear Sort Removes the sort specification for the specified column. This option works differently in the Selected Columns pane than in other places. If you make sort specifications in both the Selected Columns pane and in the view itself, then you return to the Selected Columns pane and click Clear Sort, only the sort that you specified in the Selected Columns pane is removed. A sort that you specified in the view remains. Clear All Sorts in All Columns Removes all sort specifications that you have made. This option works differently in the Selected Columns pane than in other places, as described for Clear Sort. For example, in a table in the Brand Revenue analysis, you can select an ascending sort on the Revenue column. Doing so sorts revenue values from the lowest to highest. You can sort values in the following ways: Right-click in a view heading, click Sort Column, and select the appropriate option. From the Selected Columns pane of the Criteria tab, click Options beside a column, click Sort, and select the appropriate option. 6-28 Using Oracle Business Intelligence Cloud Service

Clearing Sorts in Views You can also sort values in a view using the upwards and downward triangles that are found in column headings. Clearing Sorts in Views You can clear sorts that you have applied to columns in a view or analysis. For example, you can clear all sorts in the Time column of the Brand Revenue analysis. To clear sorts that you have applied in a pivot table, table, or trellis, right-click in the view heading and click Clear All Sorts in View. To clear sorts that you have applied to a column in an analysis: 1. Display the Selected Columns pane of the Criteria tab. 2. Click Options beside the column. 3. Select Sort, then Clear Sort. When you clear sorts from the Criteria tab, you clear only the sorts that were defined from the Column Options menu. You do not clear the sorting done within a specific view. To remove the primary sort from the column to which it now applies and apply it to the column whose button you just clicked, click a sort button in an unsorted column. Drilling in Results You can drill in results. About Drilling Topics: About Drilling Drilling in Tables and Trellises Drilling in Graphs Many of the results that are displayed in views represent hierarchical data structures. The metadata specifies these hierarchies, and this enables you to access the different Viewing Data in Different Ways 6-29

Drilling in Results levels of detail within them. Drilling is a way to navigate through data in views quickly and easily. Drill down to display data in more detail, which displays more members. Drill up to display less data. For example, in the results of the Brand Revenue analysis, you can drill for more data in the graph of Revenue by Product. To do this you can click on the MobilePhones data point. More data is displayed in the graph, such as the MobilePhones revenue per sales office for each of the last three years. Drilling in Tables and Trellises When you drill down in a table, pivot table, or trellis, the detail level data is added to the current data. For example, when you drill from a continent, the table displays data for the continent and for the countries in that continent. To drill in an attribute column in tables, pivot tables, and trellises: 1. Hover over a value in a view. The value is underlined. 2. Click the heading or member in which you want to drill. More detail is added to the table or trellis. To drill in a hierarchical column in tables, pivot tables, and trellises, click the Expand or Collapse icon beside a member. You can also use the right-click menu to expand and collapse columns. 6-30 Using Oracle Business Intelligence Cloud Service

Drilling in Results Drilling in Graphs When you drill down in a graph, the detail level data replaces the current data. For example, when you drill down from a continent, the graph displays data for the countries in that continent, but not for the continent itself. To drill in a graph: Click a label on any axis or in the legend. Click on a data point. More detail is shown in the graph. Viewing Data in Different Ways 6-31

Resizing Rows and Columns in Views Resizing Rows and Columns in Views You can resize the row and column edges of table, pivot table, and advanced trellis views. For example, you can resize the Time column in a table of results of the Brand Revenue analysis. Note that the resizing of rows and columns: Is not persisted if you resize rows and columns interactively. If you leave a table, then display it again, the interactive resizing is lost. If you set columns widths using properties, those widths are persisted. Is ignored if you export the view to PDF. Topics: Configuring for Resizing in Views Resizing in Views Configuring for Resizing in Views Resizing in Views You must configure views to use scrolling as the method for browsing data before resizing can occur. To configure a table, pivot table, or trellis view to use scrolling: 1. On the view's toolbar, click View Properties. 2. Select Fixed headers with scrolling content in the properties dialog. 3. Click OK. The scroll bar is displayed on the view, and rows and columns can be resized. You can resize a row or column edge in a table view, pivot table view, or advanced trellis. 1. Hover the mouse pointer over the border of the column or row edge. A resize cursor is displayed. 6-32 Using Oracle Business Intelligence Cloud Service

Suppressing Null Values in Views 2. Click and hold the mouse button down. A dotted line is displayed. 3. Drag the dotted line to the required size. 4. Release the mouse button. The row or column is resized. Suppressing Null Values in Views You can select whether to include null values in an analysis when an entire row or column contains all null values. By default, null measure values are suppressed for all analyses. For example, you might decide to display null values in the Revenue column of a Sales analysis. To suppress null values in views: 1. Display the Results tab for the analysis that includes the view. 2. Click View Properties. 3. Select the appropriate Include Null Values options for the view. For example, suppose that you want to turn off null suppression for both rows and columns in a pivot table. Select Include rows with only Null values and Include columns with only Null values. This setting displays corresponding dimensions that have data, as well as null values. Note that if the view contains prompts or section edges, then they also inherit the null suppression value from either the row or column edge. Note: Turning null suppression off might increase the volume of the data returned and impact performance. Contact your administrator for additional information. If results for analyses that include null values are not as you expect, then contact your administrator. Verify that data in your sources is consistent. Viewing Data in Different Ways 6-33

Assembling Views for Display Assembling Views for Display You use a compound layout to assemble different views for display on a dashboard. The views are displayed in separate containers within a compound layout. You can create additional compound layouts to vary presentation of analyses. You can use different compound layouts for different dashboards or for different devices. For example, a Brand Revenue dashboard might have one compound layout that shows a table and a graph, and another that shows a pie chart. You can duplicate a compound layout as a shortcut to creating a new compound layout. Views from the original compound layout are preserved. You can add views in addition to views that are already there, and delete views you do not want. For example, suppose you have a duplicate compound layout for the Brand Revenue analysis. You can keep the table, graph, pie chart, and gauge views, and add a performance tile view. You can rename a view so that the name is more meaningful to you. For example, for a Brand Revenue analysis, suppose a western region now consists only of California. You can rename the Western Region compound layout to California. You can delete compound layouts that are no longer useful for you. For example, for a Brand Revenue analysis, you might not need views for the Western region. You can delete the compound layout that contains those views. To create, duplicate, rename, or delete a compound layout: 1. Open the analysis for editing. 2. Click the Results tab. 3. To create a compound layout, on the toolbar of the Analysis Editor: Results tab, click on Create Compound Layout. A compound layout tab is displayed with only a title view. You can add views as needed. 4. To duplicate a compound layout, on the toolbar of the Analysis Editor: Results tab, click on Duplicate Compound Layout. A compound layout tab that contains the same views as the selected compound layout is displayed. You can add or delete views as needed. 5. To rename a compound layout, on the toolbar of the Analysis Editor: Results tab, click Rename Compound Layout. On the Rename dialog, type a new name for the compound layout and click OK. 6. To delete a compound layout, on the toolbar of the Analysis Editor: Results tab, click on Delete Compound Layout. The compound layout is removed. Linking Views in Master-Detail Relationships You can link views such that one view drives changes in one or more other views. For example, you can link two views so that when you click a particular Region in a table, your selection affects a graph. The Region on the section slider or prompt in a 6-34 Using Oracle Business Intelligence Cloud Service

Linking Views in Master-Detail Relationships graph and the data in the graph changes to reflect the Region that you clicked on the table. You must define the two types of views to link: Master view Drives data changes in one or more detail views. The following types of views can be master views: funnel graph, gauge, graph, pivot table, table, and trellis. In a trellis view, only on the outer edges, can be master views, not the inner visualizations. A master view can be the same analysis as the detail view or in a different analysis. A master view can update the data in one or more detail views. A master view contains a master column, where you set up the interaction that sends master-detail events on a channel. A channel carries master-detail events to the detail view. The master column cannot be displayed on the page edge or section slider. It must be displayed in the body of the view. Detail view Responds to master-detail events such as clicking on a value in a master view table. The following types of views can be detail views: funnel graph, gauge, graph, pivot table, table, and trellis. In a trellis view, only the outer edge can be detail views, not the inner visualizations. A detail view: Can listen for events from multiple master views Can be in the same analysis as the master view or in a different analysis Cannot act as a master view to another view Topics Defining Master Views Defining Master Views Defining Detail Views As part of the process of linking views in master-detail relationships, you define the master view that sends changes to the detail views. To define a master view: 1. Open the analysis for editing. 2. For the column that is to be the master column, in the Criteria tab, click the Options button and select Column Properties. 3. On the Column Properties dialog, click the Interaction tab. 4. In the Primary Interaction box in the Value area, select Send Master-Detail Events. 5. In the Specify channel field, enter a name for the channel on which the master view sends master-detail events. Viewing Data in Different Ways 6-35

Linking Views in Master-Detail Relationships 6. Click the Analysis editor: Results tab to view the default table or pivot table view. 7. (Optional) Create a different view to be the master view. 8. Click OK. Defining Detail Views As part of the process of linking views in master-detail relationships, you define the detail views that receive changes from the master view. To define a detail view: 1. Open the analysis for editing. 2. Click the Analysis editor: Results tab. 3. Create the view that you want to use as the detail view. 4. Edit the view. 5. Click the Property button on the toolbar of the view's editor. The view's property dialog is displayed. 6. Select Listen to Master-Detail Events on one of the following dialogs: Gauge Properties dialog: General tab Graph Properties dialog: General tab (for a graph or funnel graph) Pivot Table Properties dialog: Style tab Table Properties dialog: Style tab 7. In the Event Channels field, enter the name of the channel on which the detail view is to listen for master-detail events. The channel name is case-sensitive and must match exactly the channel name specified in the master view. Separate channels with commas, for example, channel a, channel b. 8. Click OK. In the following example, a table view of a City Revenue analysis is linked to a bar graph through a master-detail relationship. In the graph view, the City column is configured as the master view. The City column sends events to the graph view through the specified CityChoice channel. 6-36 Using Oracle Business Intelligence Cloud Service

Modifying the Layout of Data in Views The graph view has a prompt that enables users to choose a city. Data on the graph is displayed based on the city choice. The graph is the detail view, with the City prompt listening for events from the table view on the specified CityChoice channel. Suppose the user clicks on a value in the City column in the table view. The prompt in the graph view is set to that city, and the graph is refreshed. Modifying the Layout of Data in Views To modify the way that data is arranged in a view, you use the Layout pane. You perform tasks such as adding and rearranging columns and adding totals. For more information, see About Drop Targets in the Layout Pane. Topics: Adding and Rearranging Columns in Views Setting Properties for Sections of Data in Views Adding Totals to Tables and Pivot Tables Displaying Running Sums and Relative Values in Pivot Tables Adding and Rearranging Columns in Views You can add and rearrange columns in views. Topics Adding Columns to Views Removing Columns from Views Rearranging Columns in Views Viewing Data in Different Ways 6-37

Modifying the Layout of Data in Views Adding Columns to Views This topic explains how to add a column to a view. Drag the column from the Subject Areas pane to the appropriate location in the view editor. Drag the column from the Subject Areas pane and drop it on a drop target on the Layout pane of the view's editor. For example, suppose you want to include the Office column in a table of the Brand Revenue analysis. You can drag the Office column from the Subject Areas pane to a drop target after the Product column. Removing Columns from Views You can remove columns from views. Removing a column from a particular view does not remove it from the underlying analysis or remove it from other views. If you want to remove the column from the analysis and all views, remove it using the Criteria tab. To remove a column from a view: 1. Open the view for editing. 2. In the Columns and Measures section of the Layout pane, click More Options. 3. Select Remove Column. Rearranging Columns in Views You can rearrange columns in views. To rearrange table and pivot table columns in the view editor: 1. Open the view for editing. 2. Drag the column using the column handles and drop the column at a drop target. To rearrange columns in the Layout pane: 1. Open the view for editing. 2. In the Layout pane, drag and drop the column to the required location. 6-38 Using Oracle Business Intelligence Cloud Service

Modifying the Layout of Data in Views Note: This procedure provides the most basic steps for using the Layout pane to rearrange columns. Many options are available for arranging columns in the Layout pane, as described in About Drop Targets in the Layout Pane. Setting Properties for Sections of Data in Views You can specify properties for the view body (such as a pivot table) or drop target (such as a section). For example, you can set the background color to light green and insert a page break in a long table of revenue values. For information, see About Drop Targets in the Layout Pane. To set properties for view bodies and drop targets: 1. Open the view for editing. 2. In the view editor, display the Layout pane. 3. Click Properties next to the view body or drop target. 4. Set the appropriate properties. The following table describes some of the properties: Property Insert Page Break Show Blank Rows Maximum number of section slider values Description Specifies whether to create a page break before the section, so that every time a value changes in the section drop target, the new section for that column is displayed on a new page. Page breaks are visible when you export an analysis to PDF. This is useful for data-driven detail analyses. You can select from the following: No Page Break Do not break pages. Innermost Column Break at the innermost column, which inserts a page break between every section Outermost Column Break at the outermost column, which inserts a page break when the section label in the outermost column changes. When the value of an outermost column changes, the value of the inner column is also considered changed. Therefore, setting page breaks at the outermost column inserts manual page breaks between every section. Folder.Column For example, Markets.Region, or Products.Brand. Inserts a page break when the section label in the specified column changes. This option is available only when the Sections drop target contains a column. Specifies whether to display rows that have no data in the section. Select this option to display all rows, even if a row is an empty text string and contains no value. Deselect the option to hide rows when there are no results to display. This option might be useful for example, to hide empty address lines. For graphs, specifies the maximum number of values to display on a section slider bar, but not to exceed the system Viewing Data in Different Ways 6-39

Modifying the Layout of Data in Views Property Description maximum. The administrator configures the system maximum. If you enter a number that exceeds the system maximum, then it is ignored. For more information, see Defining Section Sliders in Graphs and Gauges. 5. Click OK. Adding Totals to Tables and Pivot Tables In the Layout pane, you can add totals for columns in tables and pivot tables. You can position the totals at various locations in the view. You can add totals for columns that are displayed on the various edges. For each measure, the total uses the aggregation rule for that measure. If you specify a total in the Rows or Columns drop target of a pivot table, then the totals that are displayed are the result of the columns that are specified in the Measures drop target. Total values are not displayed on the Columns or Rows edges of the pivot table but rather in the data in the center of the pivot table. To add totals to a view: 1. Display the Layout pane for the view. 2. To add grand totals to the entire table, in the Columns and Measures drop target, click the Totals button, then click the location such as Before. For an entire pivot table, in the Rows or the Columns drop target, click Totals, then the location. 3. To turn on and off the totals that apply to all the values in the drop target, click the Totals button beside the drop target name, such as Sections. Then select the location for the total, such as Before the data items. A totals area is added to the view. 4. To specify custom text to insert into a total heading in tables and pivot tables, enter text in the Caption box. The following table describes the text to enter. Text @ "@" Description Displays the value of the data. Suppose a total is specified for the Region column, and you enter the following text into the Caption box for the total heading: - All values in the @ The total heading displays the following text for the Western Region: - All values in the Western Region Displays the @ symbol. "\" Displays the double quote. The double quote syntax is not limited to a single character. In general, you can use a backslash escaped string inside double quotes. For example: "1234567890\\abc\\d\"x\"yz!@#$%ˆ&*()-+=_{}[];:'?/><,.` ~" Is displayed as: 6-40 Using Oracle Business Intelligence Cloud Service

Modifying the Layout of Data in Views Text Description 1234567890\abc\d"x"yz!@#$%ˆ&*()-+=_{}[];:'?/><,.` ~ "\\" Displays the \ symbol. \ Displays the \ symbol. Displaying Running Sums and Relative Values in Pivot Tables You can use the Layout pane to display running sums or the relative value of measure columns in pivot tables. Topics Displaying Running Sums for Measure Columns in Pivot Tables Displaying Relative Values for Measure Columns in Pivot Tables Displaying Running Sums for Measure Columns in Pivot Tables In a pivot table, you can display numeric measures as running sums, where each consecutive cell for the measure displays the total of all previous cells for that measure. This option is a display feature only that has no effect on actual pivot table results. Typically, running sums are displayed for duplicated attribute columns or for measure columns for which the option to show data as a percentage of the column has been selected, with the last value being 100 percent. For example, you can display a running sum and percentage, to view progress toward next year's revenue target of $2 million. Running sums apply to all totals. The running sum for each level of detail is computed separately. Column headings are not affected when the running sum option is selected. You can format the column heading if you want it to indicate that the running sum option is in effect. The following usage rules are in effect for running sums: A running sum is incompatible with the SQL RSUM function (the effect would be a running sum of the running sum). All running sums are reset with each new section. A running sum does not reset at a break within a section or continued across sections. If a measure does not display in a single column or in a single row, then the measure is summed left to right and then top to bottom. (The lower right cell contains the grand total.) A running sum does not reset with each row or column. To display a running sum in a pivot table: 1. Open the pivot table view in the view editor. 2. In the Layout pane, in the Measures area, click More Options for the row or column to be summed. 3. Select Display as Running Sum. Viewing Data in Different Ways 6-41

About Drop Targets in the Layout Pane Displaying Relative Values for Measure Columns in Pivot Tables In a pivot table, you can dynamically convert a stored or calculated measure into a percent or an index. This shows the relative value of the item, compared to the total, without the need to explicitly create a calculated item for it. You can view the measure as a percentage between 0.00 and 100.00, or as an index between 0 and 1. For example, if you are using a pivot table to examine sales by product, then you can duplicate the sales measure and view it as a percentage of the total. This enables you to see the actual sales, and the percentage of sales, that each product accounts for. To display relative values for measure columns in pivot tables: 1. Open the pivot table in the view editor. 2. In the Layout pane, click More Options for the item that you want to show as a relative value. 3. (Optional) To duplicate the measure column, select Duplicate Layer. The item is displayed in the pivot table, with the same name. 4. Select Show Data As. 5. Select Percent of or Index of. 6. Select the appropriate value such as Column, Row, or Section. The column is displayed in the pivot table view. 7. To rename the column, click More Options then Format Headings. In the Edit Format dialog, enter a value in the Caption field. About Drop Targets in the Layout Pane Each editor for a data view contains the Layout pane. The Layout pane is displayed slightly differently for each view type, such as graphs, performance tiles, and pivot tables. The Layout pane shows how the data in a view is laid out. In the Layout pane, the columns in a data view are displayed in drop targets. Drop targets indicate where you can insert, move, or drop a column. They represent a valid position for a column. Each drop target has properties that you can set. You use drop targets to modify the way data is arranged in a data view by dragging and dropping columns to different targets within the view. Concepts About the Types of Drop Targets About the Excluded Drop Target 6-42 Using Oracle Business Intelligence Cloud Service

About Drop Targets in the Layout Pane About the Guidelines for Drop Targets for Various Views About the Types of Drop Targets This topic describes the types of drop targets. A data view can contain one or more of the following drop targets, depending on the type of view: Target <view-type> Prompts Sections <view-type> area Description Provides an interactive result set that enables you to select the data to view. The values from the columns that are displayed in this drop target are used as the initial criteria. In a view, these values are displayed in a drop-down list for selection, which is often referred to as the "page edge." Populates the areas that divide the view into sections. If you select the Display as Slider option in this drop target, then the values of the columns that are dropped in the Sections drop target are displayed as a section slider rather than as unique views. Simulates the plot area or the body of the view itself and assists you in seeing what the view looks like. You can drag and drop columns to and from this area. In addition to the drop targets explained in the table, the Layout pane includes the Excluded drop target. (See About the Excluded Drop Target.) The Layout pane includes other drop targets that are specific to the type of view. For example, the Layout pane for the radar graph includes a Radar Sections drop target that shows the columns values as points on each line along a radius of a circle. About the Excluded Drop Target To modify the layout of data, you must understand the Excluded drop target. A column in the Excluded drop target is not included in the view results but still remains as part of the analysis. A general rule is that a column is placed in the Excluded drop target for a view if it is not added explicitly to one or all views. If you want a column that is in the Excluded drop target to be displayed in a view, then you can easily move it. Simply display the Layout pane for the view, and drag and drop the column from the Excluded drop target to the desired one. Excluding columns differs from removing columns. You can use the Remove Column option from the More Options button in the Layout pane for a view to remove a column entirely from the analysis. You place a column in the Excluded drop target after views have been created for the analysis in various ways. For example, you can select Exclude Column from the rightclick menu of a view. Suppose that you are editing a view in its editor and you add a column to that view from the Subject Areas pane. The column is placed in the Excluded drop target for all other views in the analysis. Viewing Data in Different Ways 6-43

About Drop Targets in the Layout Pane About the Guidelines for Drop Targets for Various Views As you modify the layout of views, there are guidelines that you need to bear in mind for drop targets in the Layout pane. Drop Target Guidelines for Graphs and Funnel Graphs Drop Target Guidelines for Trellises Drop Target Guidelines for Treemaps Drop Target Guidelines for Graphs and Funnel Graphs This reference describes the restrictions and guidelines that apply to dragging columns from one drop target and dropping them in another in graphs and funnel graphs. A bubble graph requires at least three measures. Plot one measure on the horizontal axis, another measure on the vertical axis, and a third measure on the bubble size axis. A pareto graph can have only one measure. If you drop another measure on the Measures drop target, then the measures are swapped; that is, the existing measure is replaced by the newly dropped measure and is moved automatically to the Excluded drop target. 6-44 Using Oracle Business Intelligence Cloud Service

About Drop Targets in the Layout Pane A time series line graph requires a single date or date-time data column to be selected on the horizontal axis. It has a single vertical axis, but supports multiple data series. A scatter graph requires at least two measures. For example, you can plot one measure column on the horizontal axis and another measure column on the vertical axis. These measures are plotted for values on the Group By axis. A funnel graph uses two measures but only one is required. If you do not select a second measure, then the first measure is used for the second measure. If you have selected two measures and then select a new measure, then the new measure replaces the measure currently in the Actual Measures drop target. A stacked bar graph requires at least two measures to allow comparison of values. Drop Target Guidelines for Trellises This reference describes the guidelines that apply to working with drop targets in trellises. In advanced trellis views, measures comprise the innermost column headers of the trellis. When moving measures from the Color By drop target to or from the Group By drop target: Dragging a single measure moves all the measures along with it. (This is known as sticky behavior.) Dragging a new measure into the view moves all existing measures to wherever you place the new measure. To place a measure on the non-measure edge of a visualization, or in the Rows target or Columns target, you must first convert the measure to an attribute column. For information, see Editing the Formula for a Column. Attribute columns can be dragged out of the Measures drop target without causing the drop target or the measures inside it to move with the attributes. Drop Target Guidelines for Treemaps You use the Layout pane areas to visualize treemaps, which are constrained, hierarchical data. You can quickly spot trends and anomalies in large quantities of data and study individual values. The Layout pane for treemaps is composed of the drop-target areas that are described in the following table: Area Prompts Sections Guidelines Select an attribute or hierarchical column (excluding ragged and skiplevel) by which to filter the treemap. Select an attribute or hierarchical column (excluding ragged and skiplevel) by which to section the treemap. For example, region that is grouped by year might be the container to display a treemap that is sized by revenue and colored by year-ago revenue. Viewing Data in Different Ways 6-45

About Drop Targets in the Layout Pane Area Group By Size By Color By Guidelines Represents the top level of the hierarchical data that is sliced to produce or describe a container of aggregated values. The aggregated values display as tiles. The group area creates a header or group for the measure columns that are specified in the Size By and Color By areas. If more than one column of data is represented in the treemap, then a title bar is displayed for the grouping. For example, region that is grouped by year might be the container to display a treemap that is sized by revenue and colored by year-ago revenue. Region displays in the title bar. Represents the distribution of the tiles within their parent. The size of the children is always equal to the size of the parent. Each rectangle's area is the aggregated value for the associated measure based on the applied filters (for example, prompted or filtered by region). Represents a distribution of values across all of the tiles at the same level and adds additional scope to the analysis providing a "qualitative" perspective to the treemap. 6-46 Using Oracle Business Intelligence Cloud Service

7 Building Dashboards This topic describes how to build dashboards to provide personalized views of corporate and external information in Oracle BI Cloud Service. Topics: Typical Workflow for Building Dashboards Creating Your First Dashboard Editing Dashboards Adding and Deleting Pages in Dashboards Preparing to Print Dashboards Organizing Dashboard Pages in Briefing Books Improving the Time to Display Dashboard Pages with Default Selections Recalling Personalized Settings Linking to Dashboard Pages Typical Workflow for Building Dashboards Here are the common tasks to start building dashboards. Task Description More Information Create multiple analyses Create a dashboard Add content to a dashboard page Add prompts to dashboard pages Add pages to a dashboard Recall personal settings for dashboards Build analyses on which you can create views that you display on a dashboard. Create a dashboard to display data from analysis. Add content to dashboard pages to display items such as views and prompts. Add prompts to dashboard pages to drive the content on the pages. Optionally add one or more pages to the dashboard to display the data in various ways. Create customizations that enable you to view pages in their current state or with your favorite choices already selected. Creating Your First Analysis Creating Your First Dashboard Adding Content to Dashboard Pages Adding Prompts to Dashboard Pages Adding Pages to Dashboards Recalling Personalized Settings Building Dashboards 7-1

Creating Your First Dashboard Creating Your First Dashboard You can create dashboards to provide personalized views of corporate and external information. A dashboard consists of one or more pages that display results of an analysis. Video Tutorial For example, you can create a Sales Performance dashboard and add content to track your team's revenue. Suppose you create three views for an analysis: performance tile view, a table view, and treemap view. You can create a dashboard that displays these three views. You can include prompts on the dashboard to enable users to specify the values to display in the views. To create a dashboard: 1. On the Home page, click Create a Dashboard. 2. In the New Dashboard dialog, enter a name and description for the dashboard. 3. Select whether to share a dashboard with others or to save it for your personal use: Shared or Personal To share with others Location To share a dashboard with others and to not list the dashboard in the Dashboard menu in the global header, save the dashboard in any level (such as /Company Shared/ Sales/Eastern). To share a dashboard with others and to list the dashboard in the Dashboard menu in the global header., save the dashboard in the /Company Shared/first level subfolder. If you specify a shared folder in which no dashboards have been saved, then a new Dashboards sub-folder is created automatically in the folder. 7-2 Using Oracle Business Intelligence Cloud Service

Editing Dashboards Shared or Personal To save for your personal use Location For example, if you select a folder named /Company Shared/ Sales in which no dashboards have been saved, a new Dashboards folder is created. The Location entry changes to / Company Shared/Sales/Dashboards. (A new Dashboards folder is not automatically created if you choose a folder at any other level.) Save the dashboard in the /MyFolders folder. 4. Specify that you want to add content to the new dashboard now. 5. Click OK. The new dashboard, which contains one blank page, is displayed in the Dashboard builder for editing. Editing Dashboards You can edit dashboards to which you have appropriate permissions and privileges. You can add or delete dashboard pages, add content such as columns and sections, and edit properties and settings such as print options. For example, you can add content to a Sales Performance dashboard to track your team's progress by adding a Brand Revenue analysis from the catalog. To edit an existing dashboard: 1. Open the dashboard. 2. Click Page Options, then select Edit Dashboard, if you have appropriate permissions and privileges. The Dashboard builder is displayed. 3. Perform one or more of the following tasks, as described in the following table: Task Add content to a dashboard page Add a dashboard page Delete a dashboard page More Information Adding Content to Dashboard Pages Adding Pages to Dashboards Deleting Dashboard Pages 4. Use the options on Tools in the toolbar of the Dashboard builder, as necessary, to perform the tasks that are described in the following table: Task Change properties Print Add to briefing book Customize a dashboard More Information Changing the Properties of a Dashboard and Its Pages Preparing to Print Dashboards Adding Content to New or Existing Briefing Books Applying Saved Customizations Building Dashboards 7-3

Adding and Deleting Pages in Dashboards 5. Perform one of the tasks that are described in the following table at any time: Task Preview Save Run Action View what the dashboard will look like when you save it. Save your changes. Exit the Dashboard builder and return to the Dashboard. Tip: You can find your current location within Oracle BI content and the path that you have used to navigate Oracle BI content. You use breadcrumbs to return to a previous location. For example, you can navigate from the Dashboard editor to the dashboard's City Revenue tab in the Sales Performance dashboard. Then you can drill into revenue by postal code for each city. For additional information, see Adding and Deleting Pages in Dashboards. Adding and Deleting Pages in Dashboards You can add and delete pages in dashboards. Topics: Adding Pages to Dashboards Adding Content to Dashboard Pages Changing the Properties of a Dashboard and Its Pages Changing the Properties of Objects Added to Dashboard Pages Deleting Objects on Dashboard Pages Deleting Dashboard Pages Adding Pages to Dashboards You can add new pages to organize content of a dashboard. For example, you can first add a new dashboard page that contains regional sales data in a table and in a bar graph. Then, you can add another that contains links to various competitors' web sites. To add a new page to a dashboard: 1. Open the dashboard for editing. 2. On the toolbar of the Dashboard builder, click Add Dashboard Page. 3. In the Add Dashboard Page dialog, enter a name and description for the page, and click OK. The page is displayed as a new tab in the Dashboard builder. 7-4 Using Oracle Business Intelligence Cloud Service

Adding and Deleting Pages in Dashboards 4. Click Save. After you add a new page, you can add content to it. See Adding Content to Dashboard Pages. Adding Content to Dashboard Pages You can add dashboard objects (any of the objects from the Dashboard objects pane) to dashboard pages. You can also add objects that you have saved in the catalog. For example, you can add content to the newly created Sales Performance dashboard to track your team's progress. To do so, you can add a Brand Revenue analysis from the catalog. To add content to a dashboard page: 1. Open the dashboard for editing. 2. Navigate to the page to which you want to add content. 3. In the Dashboard Builder, add each object that you want to include. To do so, select it in the Dashboard Objects pane or the Catalog pane and drag and drop it to the Page Layout area. The following table describes some of the objects that you can add. Object Column Section Description Add a column to align content on a dashboard. You can create as many columns on a dashboard page as you need. You can place columns horizontally or vertically. Add sections within columns to hold the content for the page, such as action links and analyses. You can include as many sections as you need for a column. 4. Set the properties of each object, as appropriate by clicking Properties. 5. To enable users to specify values to display in views on the dashboard page, include prompts as described in Adding Prompts to Dashboard Pages. 6. Click Save. Changing the Properties of a Dashboard and Its Pages You can change the style and description of the dashboard or specify links to include at the dashboard level by setting dashboard properties. For example, you can specify the options that your team members have when they view the Brand Revenue analysis on a dashboard page. You might give them options to export, refresh, and print the analysis. Building Dashboards 7-5

Adding and Deleting Pages in Dashboards To change the properties of a dashboard and its pages: 1. Open the dashboard for editing. 2. Click Tools and select Dashboard Properties. 3. In the Dashboard Properties dialog, make the property changes that you want. The following table describes some of the properties. Option Page Size Filters and Variables Dashboard Report Links Prompts Apply Buttons Dashboard Pages Description Specify whether you want the dashboard to fit content or fill the browser window. Specify to embed dashboard prompts with default values. Set the links to display with analyses on the dashboard: analyze, edit, refresh, print, export, or add to briefing book. Specify whether to show or hide Reset buttons. Hide a dashboard page, show "Add to Briefing Book," or display a prompt before opening the dashboard page. 4. Click OK, and then Save. Changing the Properties of Objects Added to Dashboard Pages You can change the properties of objects that have been added to a dashboard page. For example, you can change the column properties of the Brand Revenue analysis to specify the heading display in 14-point bold Helvetica font. To change the properties of an object on a dashboard page: 1. Open the dashboard for editing. 2. Navigate to the page that contains the object. 3. Hover the mouse pointer over the object in the Page Layout area to display the object's toolbar and click Properties. What is displayed depends on the type of object. For some objects, a properties dialog is displayed. For other objects, a menu of options is displayed. 4. Make the property changes that you want. The following table describes some properties that you can set: Dialog Break Prompt Links Action Add page and column breaks to the layout of a dashboard page. Specify whether to display the Edit link with a prompt. This link, which displays at runtime, enables users (with the proper privileges) to edit the prompt. 5. Click Save. 7-6 Using Oracle Business Intelligence Cloud Service

Adding and Deleting Pages in Dashboards Deleting Objects on Dashboard Pages Deleting Dashboard Pages If you add an object that you later decide that you do not want, then you can delete it. For example, you can delete last year's Brand Revenue analysis from the Sales Performance dashboard, to replace it with the current year's analysis. To delete an object on a dashboard page: 1. Open the dashboard for editing. 2. Navigate to the page that contains the object to delete. 3. Hover the mouse pointer over the object in the Page Layout area to display the object's toolbar and click Delete. You can delete the current dashboard page, or one or more dashboard pages. For example, you can delete pages 2 and 3 from the Sales Performance dashboard. Doing so, you retain only the page with the most recent Brand Revenue analysis. To delete the current dashboard page: 1. Open the dashboard for editing. 2. Navigate to the page to delete. 3. Click Delete Current Page. 4. Confirm the deletion. To delete one or more dashboard pages: 1. Open the dashboard for editing. 2. Click Tools and select Dashboard Properties. 3. For each page to delete: a. In the Dashboard Pages area of the dialog, select the page. b. On the Dashboard Pages toolbar, click Delete. c. Confirm the deletion. 4. Click OK. Building Dashboards 7-7

Preparing to Print Dashboards Preparing to Print Dashboards You typically view dashboards in electronic form. You can easily print a dashboard if you want to see its pages in PDF or HTML format. For example, you can print a Stock Control dashboard page so you can refer to it during a visit to a supplier's factory. At this location, no external computing devices are permitted. To print a dashboard page: 1. Open the dashboard. 2. Navigate to the dashboard page to print. 3. Click Page Options, then select Print. 4. Select Printable PDF or Printable HTML. 5. Open Adobe Acrobat or a browser window and print from there. Organizing Dashboard Pages in Briefing Books You can organize dashboard pages in briefing books. Topics: Adding Content to New or Existing Briefing Books Editing the Content of Briefing Books Downloading Briefing Books Adding a List of Briefing Books to a Dashboard Page Adding Content to New or Existing Briefing Books You can add the content of dashboard pages or individual analyses to new or existing briefing books. A briefing book is a collection of static or updatable snapshots of dashboard pages and individual analyses. For example, you can add the contents of the Regional Revenue analysis to a briefing book each quarter. This process enables you to review quarterly snapshots of the data. 1. Open the dashboard. 2. Navigate to the page to add or that contains the analysis to add. 3. To add the contents of the dashboard page to a briefing book, click Page Options and select Add To Briefing Book. 4. To add the results of an individual analysis to a briefing book, edit the dashboard, select Tools, and select Page Report Links. Select the Customize option and click Add to Briefing Book. 5. In the Save Briefing Book Content dialog, click Browse. 6. In the Save As dialog, specify the appropriate location for the briefing book: 7-8 Using Oracle Business Intelligence Cloud Service

Organizing Dashboard Pages in Briefing Books Location New briefing book Existing briefing book Description Specify the location in which to save the briefing book in the Save In field. Enter a name for the briefing book in the Name field. Optionally enter a description in the Description field, and click OK. Select the briefing book and click OK. 7. In the Save Briefing Book Content dialog, complete the remaining fields as appropriate. 8. Click OK. Editing the Content of Briefing Books You can edit briefing books to reorder content, delete content, and change the content type, navigation link properties, and content description. For example, you can edit a briefing book to change the content description to reflect the periods of Brand Revenue analysis data. To edit a briefing book: 1. In the global header, click Catalog to display the Catalog page. 2. Navigate to the briefing book to edit and click Edit. 3. In the Edit Briefing Book dialog, to change content: a. Select the content. b. Click Edit Page to display the Page Properties dialog. c. Change the content type, the number of navigation links to follow for updatable content, or the content description as needed. d. Click OK. 4. To reorder content, select the content and then drag and drop it to the desired location. 5. To delete content, select the content and click Delete. Building Dashboards 7-9

Organizing Dashboard Pages in Briefing Books 6. Click OK. Downloading Briefing Books You can download briefing books. You can: Download briefing books to your computer in MHTML format and then share them for offline viewing. Download briefing books in PDF format and print them. The PDF version of a briefing book contains an automatically generated table of contents. For example, you can download a briefing book that contains all the Brand Revenue analyses for the year. After downloading, you can view the briefing book in Adobe Reader and print it in preparation for a sales presentation. To download a briefing book: 1. In the global header, click Catalog to display the Catalog page. 2. Navigate to the briefing book to download. 3. Perform one of the following actions: To download the briefing book in PDF format, click PDF and open or save the file. Note: The Adobe Reader application is required to view or print a briefing book PDF file. To download the briefing book in MHTML format, click Web Archive (.mht) and open or save the file. Downloaded briefing books are saved with an.mht file extension and can be opened in a browser. You can then email or share the briefing book. Adding a List of Briefing Books to a Dashboard Page You can add a list of briefing books to a dashboard page. For example, you can add a list of briefing books that contain Brand Revenue analyses to a Sales Performance dashboard page. To add a list of briefing books to a dashboard page: 1. Open the dashboard for editing. 2. Navigate to the page to which you want to add a list of briefing books. 3. From the Dashboard Objects pane, drag and drop a folder object into a section. 4. Hover the mouse pointer over the folder object in the Page Layout area to display the object's toolbar and click Properties. 7-10 Using Oracle Business Intelligence Cloud Service

Improving the Time to Display Dashboard Pages with Default Selections 5. In the Folder Properties dialog, in the Folder field, enter the folder that contains the briefing books to list. 6. In the Expand box, specify whether to show an expanded view of the folder. 7. Click OK and click Save to save the dashboard. Improving the Time to Display Dashboard Pages with Default Selections You can improve the time that it takes to display dashboard pages. Under certain circumstances, dashboard pages might take several moments to display in a browser. When the pages are displayed, they might not show the values that users had wanted to see in analyses based on the selection of prompts. You can enable users to specify prompt values (rather than using default prompt values) before analyses content is displayed on dashboard pages. This confirmation in displaying content initially improves the wait time for displaying the page with default prompt selections. The content of analyses is not displayed on the page until the user responds to prompts. Other objects (such as dashboard prompts, text, and so on) are displayed For example, you can prompt for which regions to include before displaying the Brand Revenue analysis on the Sales Performance dashboard page. When you prompt users for values before displaying analyses, the following occurs: A message is displayed at the top of the page, which indicates that the page is not fully loaded. The message also instructs the user to select prompt values and click Continue. Clicking Continue displays the content on the page using the prompt values that the user specifies. If the user does not specify any prompt values, then the analysis is displayed with default prompt values. The page displays static information about the objects that have not yet been displayed. The information includes the object name, an icon that represents the object view, the view name, and the object description (if available). On the Page Options menu (displayed from Page Options on the Dashboard page toolbar), all options except Edit Dashboard are disabled. The Apply button on dashboard prompts is not displayed. Instead any prompt values are applied automatically when the user clicks Continue. To improve the time to display a dashboard page: 1. Open the dashboard for editing. 2. Click Tools and select Dashboard Properties. The Dashboard Properties dialog is displayed. 3. Locate the page in the Dashboard Pages area and select Prompt before Opening. Building Dashboards 7-11

Recalling Personalized Settings 4. Click OK. 5. Click Save. Recalling Personalized Settings You can recall personalized settings that you made for dashboard pages. As you work with dashboard pages, you frequently make the following types of settings: Filters Prompts Column sorts Drills in analyses Section expansion and collapse These personalized settings are not saved when you close the dashboard. To have the ability to recall these personalized settings, you save the settings as a customization. Saved customizations enable you to save and view later dashboard pages in their current state with the most frequently used choices for items. By saving customizations, you need not make these choices manually each time that you access the dashboard page. Topics: Saving Customizations of Dashboard Pages Applying Saved Customizations Editing Saved Customizations Clearing the Current Customization Saving Customizations of Dashboard Pages You can save customization for use by you or by others who have author, but not a consumer, role. You can also specify whether the customization is to be the default customization for a dashboard page, for you or for others. For example, you can save a customization of the Sales Performance dashboard. The customization enables sales managers with permission to see a customized view of the Brand Revenue analysis. To save a customization: 7-12 Using Oracle Business Intelligence Cloud Service

Recalling Personalized Settings 1. Open the dashboard. 2. Navigate to the page on which you want to save a customization. 3. Make your personalized settings. 4. Click Page Options and select Save Current Customization. 5. Enter a descriptive name for the customization in the dialog. 6. Specify for whom the customization is to be saved. For Whom For your personal use For use by others Action Select ME. Select Others and click Set Permissions. Specify the author accounts that have permission to use the customization. 7. To assign a customization as default, select Make this my default for this page. 8. Click OK. Applying Saved Customizations You can apply customizations that you have saved for your own personal use. You can also apply customizations that have been saved by someone else for your use. For example, you can apply a shared Sales Team customization that was created for customized viewing of a Brand Revenue analysis by members of the sales team. To apply a saved customization: 1. Open the dashboard for editing. 2. Navigate to the page that contains the customization to apply. 3. Click Page Options and select Apply Saved Customization. Your personal saved customizations are shown, followed by shared saved customizations. Your current default customization is shown in bold. 4. Click a saved customization in the list to apply it to the dashboard page. Building Dashboards 7-13

Linking to Dashboard Pages Editing Saved Customizations You can rename and delete customizations and change which customization to use as your default. For example, you can change your default customization to one that you just saved for the Sales Performance dashboard. To edit saved customizations: 1. Open the dashboard for editing. 2. Navigate to the page that contains the customization to edit. 3. Click Page Options and select Edit Saved Customizations. 4. Rename or delete customizations or change the default customization, as appropriate. 5. Click OK. Clearing the Current Customization You can clear the current customization if you decide that the choices for items such as filters, prompts, column sorts, drills in analyses, and section expansion and collapse are not what you want. For example, you can clear a customization that collapses the display of the Brand Revenue analysis. To clear the current customization, click Page Options and select Clear My Customization. The current customization is cleared. Linking to Dashboard Pages You can create links to dashboard pages so that you can easily enable other users to display those pages. For example, you can create a link to the Sales Performance dashboard and send the link to team members in an email. Topics: About Bookmark Links About Bookmark Links Creating Links to Dashboard Pages A bookmark link is a URL that captures the path to a dashboard page and all aspects of the page state. After you create a bookmark link, you can: Save the link as a bookmark so that you can return to the exact same page content at a later time. Copy and send the link to other users who then can view the exact same content that you are viewing. They can do this providing they have the same permissions as you and have access to the page. 7-14 Using Oracle Business Intelligence Cloud Service

Linking to Dashboard Pages When you create a bookmark link, the state of a dashboard page is saved in the catalog as a hidden bookmark object. The default number of days to save the object is 30. Creating Links to Dashboard Pages You can create links to dashboard pages. To create a link to a page in a dashboard: 1. Open the dashboard. 2. Navigate to the page for which you want to create the link. 3. From the Page Options menu, select Create Bookmark Link. Note: You can drill in an analysis that has been set to replace the dashboard with the new results. You can do the replacement rather than showing the new results directly in the dashboard. In this case, the Create Bookmark Link option is displayed as a link below the new results. The option is not displayed on the Page Options menu. The link is displayed in the Address Bar of the browser. If the link is a bookmark link, then you can save it as a bookmark or copy and send it to other users. Building Dashboards 7-15

8 Filtering and Selecting Data for Analyses This topic describes how to filter and select data for analyses. Topics: Typical Workflow for Filtering and Selecting Data About Filters and Selection Steps Creating Filters for Columns Editing Filters for Columns Reusing Filters Using a Saved Analysis as a Filter Advanced Techniques: How Dashboard Prompts and Analysis Prompts Interact Refining Selections of Data Manipulating Members Using Groups and Calculated Items Typical Workflow for Filtering and Selecting Data Here are the common tasks to start filtering and selecting data to display in analyses. Task Description More Information Create an analysis Create a filter Edit a filter Save a filter Create a selection step Create a group Select and arrange columns that you want to use in an analysis. Limit the results that are displayed when an analysis runs. Change the operator and values in a filter. Save filters in the catalog or with the analysis. Select members, new groups, existing groups, new calculated items and conditions for displaying data. Group column values for display in an analysis. Creating Your First Analysis Creating Filters for Columns Editing Filters for Columns Saving Filters Creating Selection Steps Creating Groups and Calculated Items Filtering and Selecting Data for Analyses 8-1

About Filters and Selection Steps Task Description More Information Create a calculated item Apply a function to column values to calculate a new value. Creating Groups and Calculated Items About Filters and Selection Steps You use both filters and selection steps to limit the results that are displayed when an analysis is run. About Prompted Filters This means that the results answer a particular question. Together with the columns that you select for an analysis, filters and selection steps determine what the results contain. Based on the filters and selection steps, only those results that match the criteria are shown. For example, depending on the industry in which you work, you can use filters and selection steps to learn who are the top ten performers. You can also learn the dollar sales for a particular brand, and which are the most profitable customers. Filters and selection steps are applied on a column-level basis and provide two methods for limiting the data in an analysis. A filter is always applied to a column before any selection steps are applied. Steps are applied in their specified order. Filters and selection steps differ in various ways: Filters are applied directly to columns before the query is aggregated. Filters affect the query and thus the resulting values for measures. For example, suppose that you have a list of members in which the aggregate sums to 100. Over time, more members meet the filter criteria and are filtered in, which increases the aggregate sum to 200. Selection steps are applied after the query is aggregated and affect only the members displayed, not the resulting aggregate values. For example, suppose that you have a list of members in which the aggregate sums to 100. If you remove one of the members using a selection step, then the aggregate sum remains at 100. Selection steps are per column and cannot cross columns. Another kind of filter, called a prompt, can apply to all items in a dashboard. Prompts can be used to complete selection steps and filters at runtime. For information, see Prompting in Analyses and Dashboards. A prompted filter is a filter whose operator is set to is prompted. This operator is valid for a column that contains text, numbers, or dates. When you select the is prompted operator for a filter's column, you flag the column as ready to be filtered by a prompt. When a prompt is used, results include only records where the data in the column that is prompted matches the user's choices. The is prompted operator is required for columns that are included in prompts where no prefiltered values are wanted. For more information, see Specifying Values for Filters and Advanced Techniques: How Dashboard Prompts and Analysis Prompts Interact. Creating Filters for Columns You can create filters for columns. Video 8-2 Using Oracle Business Intelligence Cloud Service

Creating Filters for Columns Topics: Creating Inline and Named Filters Specifying Values for Filters Saving Filters A filter limits the results that are displayed when an analysis is run. Together with the columns that you select for the analysis, filters determine what the results contain. You specify filter criteria to display only the results that you want to show. For more information, see About Filters and Selection Steps. Creating Inline and Named Filters In most cases, you create and include a filter "inline" for use in only one analysis. You can also create a named filter to reuse the filter across all analyses and dashboards. Unless you want to reuse the filter, create an inline filter. For example, as a sales consultant, you can filter the results that are shown in an existing Brand Revenue analysis. In this way, you can see revenue for only those brands for which you are responsible. To create an inline filter from the Selected Columns pane on the Criteria tab: 1. Open the analysis for editing. 2. On the Selected Columns pane of the Criteria tab, click Options beside the column name and select Filter. The New Filter dialog is displayed. See Specifying Values for Filters. To create an inline filter from the Filters pane on the Criteria tab: 1. Open the analysis for editing. 2. On the Filters pane of the Criteria tab, click Create a filter for the current Subject Area. 3. Select a column name from the menu. The New Filters dialog is displayed. See Specifying Values for Filters. To create a named filter: 1. On the toolbar, click New and select Filter. 2. In the Subject Areas pane, double-click a column. Filtering and Selecting Data for Analyses 8-3

Creating Filters for Columns Specifying Values for Filters The New Filter dialog is displayed. See Specifying Values for Filters. You can specify the values for a filter that displays in an analysis only those values in which you are interested. For example, in the Brand Revenue analysis, a filter can limit the analysis results to only the first quarter values in three years. As a result, you can discover how revenue performed year-to-year in these quarters. To specify values for a filter: 1. Complete one of the procedures as described in Creating Filters for Columns. 2. In the New Filter dialog, select the appropriate operator such as is equal to / is in. See About Prompted Filters for information about the is prompted operator. 3. Select values from the list or click the Search icon to find more values from which to select. 8-4 Using Oracle Business Intelligence Cloud Service

Creating Filters for Columns 4. (Optional) Select Protect Filter to prevent prompts from overwriting the filter. For information, see Editing Filters for Columns. 5. (Optional) Select Convert this Filter to SQL. For information, see Editing Filters for Columns. 6. Click OK. For inline filters, the filter is displayed in the Filters pane on the Criteria tab. For named filters, the filter is displayed in the Saved Filters pane. Saving Filters After specifying values, save the filter as named or inline, as described in Saving Filters. You can save inline filters and named filters. When you create an inline filter in the Filters pane, you can optionally save the inline filter as a named filter. When you save an inline filter as a named filter, other people on your team can use this filter in a new analysis. You can also create a named filter as a standalone object from the global header. For example, you can save a filter for the Quarter column in a shared folder in the catalog. As a result, your manager has access to that filter. Suppose that you save the filter that limits quarters to 2011 Q1, 2012 Q1, and 2013 Q1. Your manager can use this filter in a Product Revenue analysis to find how products performed only during these quarters. To save an inline filter as a named filter: 1. On the Filters pane on the Criteria tab, click More options and select Save Filters. Filtering and Selecting Data for Analyses 8-5

Editing Filters for Columns 2. Specify a folder in the Oracle BI Presentation Catalog. 3. Click OK. To save a named filter: 1. On the toolbar, click Save As. 2. Specify a folder in the Oracle BI Presentation Catalog. 3. Click OK. Editing Filters for Columns You can edit an inline filter when you need to make changes to it. When you edit and save a named filter, the changes that you make to the filter propagate to wherever the filter is used. For example, you can edit the filter for the Quarter column to include data for the "2010 Q1" quarter. This data is propagated to every analysis where the filter is applied. To edit an inline filter: 1. Display the Edit Filter dialog. For example, on the Saved Filter pane or in the Filters pane of the Criteria tab, hover the cursor over the filter, then click Edit Filter. 2. In the Edit Filter dialog, change the selection for any of the options that are described in the following table: Option Operator Value Protect Filter Description Select an operator to apply to the values that are specified in the Value field. The Operator list is populated based on the function that you are performing (such as creating a filter or creating a dashboard prompt). It is also populated based on the type of column that you selected. For example, you can choose is greater than to use only values greater than the value that you select in the Value list. If you select 100,000 from the Value list, then the filter uses values from the column that are greater than 100,000. You can use this information in an analysis to focus on products that are performing best. Specify a value or values from the list that contains members of the column that you select. You can also enter the value into the field manually or search. For example, suppose that you want to edit a filter that you have created for the Products column of an analysis. The Value field contains a list of products from the column. Depending on the operator that you chose, you can select one or more products to include in the analysis. Select this option to prevent prompts from overwriting the filter. 8-6 Using Oracle Business Intelligence Cloud Service

Reusing Filters Option Convert this Filter to SQL Description Select this option to convert the filter to a SQL WHERE clause that you can edit manually. After you convert a filter to SQL code, you can no longer view and edit the filter in the Edit Filter dialog. 3. Click OK. Reusing Filters You can reuse a filter that you have saved as a named filter in the catalog. You can apply a saved filter to an existing analysis. For example, you can apply a filter for the Quarter column to the Brand Revenue analysis. To reuse a named filter: 1. On the Catalog pane on the Criteria tab, select a named filter. 2. Click Add More Options. The Apply Saved Filter dialog is displayed. 3. (Optional) Add the named filter in both or either of the following ways: Filtering and Selecting Data for Analyses 8-7

Using a Saved Analysis as a Filter Option Clear all existing filters before applying Apply contents of filter instead of a reference to the filter Description Select this option to remove all existing filters from the analysis before adding the saved filter. Select this option to add the filter as an inline filter. The filter is added to the Filters pane on the Criteria tab, where you can edit it. Any changes that you make to the filter are saved with the analysis, but not with the catalog. Deselect this option to add the filter as a named filter. The filter is added to the Filters pane on the Criteria tab, where you can view it but not edit it. 4. Click OK. Using a Saved Analysis as a Filter You can create a filter based on the values that are returned by another analysis. You can use any saved analysis that returns a column of values to filter the matching column in an analysis. For example, you can create a filter that is based on the results of the Brand Revenue analysis. To create a filter based on the results of another saved analysis: 1. Create or open a named filter or analysis to which you want to apply an inline filter. 2. Find the filter. If you are working with a named filter, then locate the Saved Filter pane. From the Subject Areas pane, select the column for which you want to create a filter. If you are working with an inline filter, then locate the Filters Pane. From the Filters Pane toolbar, click Create a filter for the current Subject Area. Select the column for which you want to create the filter. The New Filter dialog is displayed. 3. In the Operator field of the New Filter dialog, select is based on the results of another analysis. 4. In the Saved Analysis field, enter the path to the analysis or click Browse to locate it. 5. Select a column name from the Use Values in Column menu. 6. In the Relationship field, select the appropriate relationship between the results and the column to be filtered. 8-8 Using Oracle Business Intelligence Cloud Service

Advanced Techniques: How Dashboard Prompts and Analysis Prompts Interact 7. Click OK. Advanced Techniques: How Dashboard Prompts and Analysis Prompts Interact You can combine and wire prompts in various ways to create dashboards that enable users to quickly and easily request precise, meaningful data. Most people don t need to perform this task. Combining and wiring prompts enables you to specify how dashboard prompts interact with analysis prompts. Variable prompts cannot be combined or wired. For example, you can create analysis A that contains information about the amount of product that is sold by region. To the Region column, add the Is protected option and then add a Region prompt. You can then create analysis B that contains information about sales person by region. You can also create analysis C that contains information about city by region. You then create and save a dashboard prompt for Region. You create a dashboard and add analyses A, B, and C and the Region dashboard prompt. When you run the dashboard, the dashboard prompt input drives only what is displayed in analyses B and C. In this scenario, analysis A does not use the Region value that is specified in the dashboard prompt. This is because you set analysis A's Region column filter value to Is protected. The only way that analysis A accepts a prompt value is if the user specifies a prompt value in Region A's prompt fields. There are various ways that you can combine and wire prompts, as described in the following table. Wiring Method Auto wiring Constrained prompts Filter operator is set to is Prompted. Selection Steps Override with Prompts Option Description The auto wiring functionality assumes that you intended to create a functioning prompt for the column and, therefore, activates and applies the prompt. Oracle BI Cloud Service applies the auto wiring method when you create an analysis and add a column prompt. This auto wiring method does not require the is prompted filter operator. Any unprotected filter can be used. Setting the filter operator to is prompted provides a more precise level of control between prompts and filters than the auto wiring method. For more information, see the "Filter operator is set to is prompted" row in this table. Use this method with several columns in a prompt to constrain the user's prompt choice based on subsequent choices. Constrained prompts can be set up on the Prompt options dialog to specify which prompt narrows the choices. For example, suppose one column filters on region and the next column filters on city. Then, the city column can be constrained to show only cities in the selected region. Use this method to build complex prompts that interact with filters. When you use this method, you have full control over how the dashboard prompts, inline prompts, and filters apply to the embedded analysis. For information, see About Prompted Filters. Use this method to use an analysis or dashboard column prompt to provide the data choices for a specific member selection step. Because you cannot use filters with hierarchical Filtering and Selecting Data for Analyses 8-9

Refining Selections of Data Wiring Method Protected versus Unprotected filters Description columns, selection steps are the only way that you can use prompts with hierarchical columns. Only one selection step per column selection step set can be overridden with a prompt. All selection steps before and after the overridden step are processed as specified. For more information about selections steps, see Refining Selections of Data. For more information about creating a prompt that works with selections, see Overriding a Selection Step with a Prompt. Use this method to determine whether the dashboard prompt can supply the inline prompt's value when the corresponding column's filter value is set to something other than Is prompted. The unprotected and protected filter settings can be used when a dashboard prompt and inline prompt reside on the same dashboard. Also, both prompts must have been created for the same column. When the column's filter value is unprotected, the dashboard prompt value determines the analysis' results. Suppose the filter value is set to something other than Is prompted (for example, Is equal to/is in) and the filter is set to protected filter. Then, the dashboard prompt cannot determine the report results. Refining Selections of Data As you specify which data members to include in an analysis, you create selections of data from the data source. Each selection specifies the criteria for a set of members for a particular column, such as Product or Geography. Each selection consists of one or more steps. A step is an instruction that affects the selection, such as add Product members whose values contain the text "ABC." The order in which steps are performed affects the selection of data. Each step acts incrementally on the results from previous steps, rather than acting on all the members for that column. For more information, see About Filters and Selection Steps. Topics: Creating Selection Steps Creating Selection Steps Editing Selection Steps Saving Selection Steps for Reuse Advanced Techniques: Creating Condition Steps You create a selection step to provide the instructions for specifying the criteria for selections of data from the data source. When you add a column to an analysis, an 8-10 Using Oracle Business Intelligence Cloud Service

Refining Selections of Data implicit "Start with all members" step is added. The "all" implies all the members of the column after filters are applied. For example, you can create a selection step to specify criteria for the following members in an Office column: Baltimore, Austin, and Athens. To create a selection step for an analysis: 1. Open the analysis for editing. 2. Select the Criteria tab. 3. Display the Selection Steps pane by clicking Show Selection Steps Pane on the toolbar. 4. Click Then, New Step, and select the kind of step to create. For example, you can specify a list of selected members for the step. Depending on your selection, the New Member Step, New Select Existing Groups and Calculated Items, New Group, New Calculated Item, or New Condition Step dialog is displayed. 5. For a member step, select Add, Keep Only, or Remove from the Action list. The following table describes what you can do with these options: Option Add Keep Only Remove Description Use this option to add the selected members to the selection. Use this option to keep only the selected members and remove all others. For example, you can keep only the sales that are generated by a selected Sales Associate. Use this option to remove the selected members from the selection. For example, you can remove the Eastern and Western regions from the selection. 6. If you are creating a member step, then move the members to include in the step from the Available area to the Selected area. Filtering and Selecting Data for Analyses 8-11

Refining Selections of Data 7. For a step that involves a group or calculated item, select an existing group or calculated item or create a new one. 8. If you are creating a step that involves a condition, then select the appropriate condition type. For example, select X>=Y to correspond to something like Sales >= Costs. For more information, see Advanced Techniques: Creating Condition Steps. 9. Specify the appropriate values for the condition such as the action, measure, and operator to use for the values of the column. 10. Click OK. Editing Selection Steps You can edit existing selection steps. For example, you can edit a member step for the Offices column in the Brand Revenue analysis. You can add Augusta to the list of cities. To edit a selection step for an analysis: 8-12 Using Oracle Business Intelligence Cloud Service

Refining Selections of Data 1. Open the analysis for editing. 2. Click on the Results tab. 3. On the Selection Steps pane, hover the mouse pointer over the selection step that you want to edit. 4. Click the pencil icon on the toolbar. A dialog is displayed to correspond to that type of selection step. 5. Perform the appropriate edits. For example, add one or more members from the column to the step. 6. Click OK. To edit a selection step that has been saved as a group object: 1. In the Catalog pane, navigate to the location of the saved object. 2. On the Catalog pane toolbar, click Edit. 3. On the in the Edit Group dialog, perform the appropriate edits. 4. Click OK. Saving Selection Steps for Reuse If you have created a set of selection steps, then you can reuse them if you save them as a group in the catalog. For example, you can reuse the selection steps for the Offices column as a group object. Doing this enables the set to be used inline with the Brand Revenue analysis. Note: You can save a set of selection steps only if the set includes more than just a single Start With step in the list for a column. You cannot save a set of steps if one of the steps includes a calculated item. For more information about reusing groups, see Reusing a Group or Calculated Item in an Analysis. To save selection steps as a group object: 1. Open the analysis for editing. 2. On the Results tab, display the Selection Steps pane. 3. Click Save Selection Steps to the far right of the column name. The Save Selection Steps dialog is displayed. 4. In the Save In field, specify a location where you want to save the selection steps. If you want to keep the filter for your personal use, then save it in /My Folders/ subfolder. If you want to share the filter with others, save it in /Company Shared/ subfolder. 5. Enter a name for the saved selection steps. Filtering and Selecting Data for Analyses 8-13

Refining Selections of Data 6. Click OK. The selection step is saved as an object in the catalog. Advanced Techniques: Creating Condition Steps One type of selection step that you can create is a condition step. Most people don t need to perform this task. You specify that members are selected from a column based on a condition. The condition can be one of various types including based on measures or on top/bottom values. This member list is dynamic and determined at runtime. For example, you can select the top 5% of members based on Brand Revenue. For the general procedure for creating selection steps, see Creating Selection Steps. To create a condition step: 1. Open the analysis for editing. 2. Select the Criteria tab. 3. Display the Selection Steps pane by clicking Show Selection Steps Pane on the toolbar. 4. Click Then, New Step, then select Apply a Condition. 5. In the New Condition Step dialog, select the type of condition to create, as described in the following table. Type Exception Top/Bottom Match Time/Ordinal Description Select members using comparison values for measure columns. A sample condition is "Sales > Cost +10%." Select the specified number of members after ranking the members by the specified measure column. You can specify an exact number of members or a percentage of the total members. Sample conditions are "Top 10 based on Sales" and "Top 5% based on cost. Select members based on matches with text strings and attribute values. A sample condition is "Name contains abc." This type is available only for columns that have a data type of string. Select members based on ranges of time and on hierarchical levels. A sample condition is "From July 2012 to December 2012." This type is available only for columns with a data type that relates to time. 8-14 Using Oracle Business Intelligence Cloud Service

Refining Selections of Data The components in this dialog differ slightly, depending on which type you select. 6. In the Action box, select the type of action to create for the members. You can select to add the selected members to the selection, keep only the selected members and remove all others. Or, you can select to remove the selected members from the selection. 7. In the box beside the action type, select the column for whose members you are creating the condition step. 8. Enter the appropriate values for the various fields of the dialog. For example, select the Operator based on the type of condition. For example, select Within for the Exception type. 9. Use the Override with box to specify whether an analysis prompt, a dashboard prompt, or a variable can override the values that you specify in this condition. Depending on what you are overriding, you can override certain values with a prompt, a presentation variable, a session variable, or a repository variable. If you select a variable type, then enter the name of the variable in the field. For example, suppose that you have a column called EMPLOYEE_ID. You can specify USER as the session variable with which to override the value of that column. When a user signs in, the column value is set to his user name. For more information on variables, see Advanced Techniques: Referencing Stored Values in Variables. In a list of steps, specify that only one step in the list can be overridden by a prompt or presentation variable. 10. In the For area, qualify all of the dimensions of the analysis other than the dimension whose members you want to select. Do this when creating condition steps of type Exception or Top/Bottom. For each dimension, you select which of its members to include. You can select specific members, or All, which specifies to aggregate the members when creating the condition. For example, suppose that you are qualifying the Region dimension. You can select a specific region, such as East, whose value is used in the New Condition Step dialog condition. If you select All, then the values of all regions are aggregated and used in the condition. You can use the For area to create a qualified data reference (QDR). A QDR is a qualifier that limits one or more of the dimensions to retrieve a single value for a Filtering and Selecting Data for Analyses 8-15

Manipulating Members Using Groups and Calculated Items measure column. A QDR is useful when you want to temporarily reference a measure column value without affecting the current status of the dimensions. The following is an example of a QDR: Add members of Total Products (Rgd Sk Lvl) where "A - Sample Sales"."Base Facts"."1- Revenue", For: Cust Segments Hier: 'Active Singles', 'Baby Boomers' is greater than "A - Sample Sales"."Base Facts"."1- Revenue", For: Cust Segments" When you specify a QDR, you can specify multiple members for limiting the dimensions. When you specify multiple members, the measure column value is aggregated using the default aggregation. For example, suppose that you want to create a condition for displaying those Regions in which Units is greater than 100. Suppose that you create a QDR for the Year dimension that specifies 2010 and 2011 and that the default aggregation is Sum. If the values for 2010 and 2011 for the Central region are 50 and 60 respectively, then both those years are displayed. Their sum exceeds the 100 units that were indicated. 11. Click OK. Manipulating Members Using Groups and Calculated Items You can manipulate members using groups and calculated items. Topics: About Groups and Calculated Items Creating Groups and Calculated Items Editing Groups and Calculated Items Viewing Group Contents Saving Groups and Calculated Items Reusing a Group or Calculated Item in an Analysis Deleting Groups and Calculated Items About Groups and Calculated Items You can create a group or calculated item as a way to display data in a table, pivot table, trellis, or graph. Groups and calculated items enable you to add new "members" to a column, when those members do not exist in the data source. These members are also known as "custom members." Use a group to define members of a column, as a list of members or a set of selection steps that generate a list of members. A group is represented as a member. A calculated item is a computation between members, which is represented as a single member that cannot be drilled. When you create a calculated item, you add a new member in which you have selected how to aggregate the item. You can aggregate using Sum or Average or custom formula. 8-16 Using Oracle Business Intelligence Cloud Service

Manipulating Members Using Groups and Calculated Items Creating Groups and Calculated Items Use a group or calculated item to add new "members" to a column. For example, you can review how much revenue was generated for mobile devices and compare that number to other product types. You can create a group called Mobile Devices for the Product column that includes Flip Phones and Smart Phones. Video To create a group or calculated item for an analysis: 1. Open the analysis for editing. 2. On the toolbar of the Results tab, click New Group or New Calculated Item. The New Group or New Calculated Item dialog is displayed. 3. Enter a value for Display Label for the group or calculated item when it is displayed in a view. 4. In the Values From list, select the column whose values you want to include in the group or calculated item. 5. If you are creating a calculated item, select the function for the calculated item. 6. Move the appropriate column values from the Available area to the Selected area. 7. For a calculated item with Custom Formula selected as the function, select mathematical operators to include in the function using the toolbar. You can also use these functions: Absolute, Ceiling, Floor, Round, and Sqrt. A formula creates a dynamic custom grouping within the view. All measures referenced in a formula must be from the same column and must be present in the results. Formulas can be inserted into, or combined with, other calculated items. Instead of specifying a named item for columns, you can specify $n or $-n. Here, n is an integer that indicates the item's row position. If you specify $n, then the Filtering and Selecting Data for Analyses 8-17

Manipulating Members Using Groups and Calculated Items measure is taken from the nth row. If you specify $-n, then the measure is taken from the nth to the last row. 8. (Optional) If you are creating a calculated item, select Remove calculated item members from view. Use this box to suppress the display of members that you have included in the calculated item in the view. 9. Click OK. By default, the new group or calculated item is created for all views in the analysis. Editing Groups and Calculated Items You can edit groups and calculated items through the Selection Steps pane or from the catalog pane. You can also edit groups and calculated items in a table, pivot table, or trellis. For example, you can edit a group to include the Game Station and Plasma Television members. To edit a group or calculated item, use one of the following ways: Location In the Selection Steps pane In the Catalog pane (if you saved it in the Catalog) In a table, pivot table, or trellis (on an outside edge) Step Click the link to the group or calculated item and click Edit. Select the object and click Edit. Right-click the group or calculated item and select Edit Group or Edit Calculated Item. 8-18 Using Oracle Business Intelligence Cloud Service

Manipulating Members Using Groups and Calculated Items Viewing Group Contents You can view the contents of a group to verify that it contains the members that you want. For example, suppose you created a group of categories in a Product Category column. You can view the group contents to verify that it contains the appropriate categories. To view the contents of a group: 1. Open the analysis for editing. 2. Click on the Analysis Editor: Results tab. 3. In the table view, right-click on the cell that contains the group. 4. Select View Group Definition. The View Group dialog is displayed. 5. Click Close. Saving Groups and Calculated Items You can save a group or calculated item as either an inline object (with an analysis) or as a named object (a standalone object). For example, you can save the Mobile Devices group as a named object in the catalog, for reuse in the Brand Revenue analysis. To save a group or calculated item as an inline object: 1. Create the group or calculated item, as described in Creating Groups and Calculated Items. 2. To save the analysis and the group or calculated item that it contains, click Save Analysis. The group or calculated item is saved as a part of the analysis. To save a group or calculated item as a named object: 1. Create the group or calculated item, as described in Creating Groups and Calculated Items. 2. On the Analysis Editor: Results tab, display the Selection Steps pane. 3. Click the link for the group or calculated item. 4. Select Save Group As or Save Calculated Item As. The Save As dialog is displayed. Filtering and Selecting Data for Analyses 8-19

Manipulating Members Using Groups and Calculated Items 5. Enter a folder in the Save In field. If you want to save a group or calculated item for your own use, then save it in a /My Folders/subfolder. If you want to share the group or calculated item with others, then save it in a /Company Shared/ subfolder. 6. Enter a group or calculated item name (required) and a description (optional). 7. Click OK. The group or calculated item is saved in the catalog as an object. Reusing a Group or Calculated Item in an Analysis You can add a group or calculated item to the same column on which it was created in another analysis. The group or calculated item can be either a list of members or a set of selection steps. For example, you can display the Brand Revenue analysis and add the group members from the Mobile Devices group. The members of the Mobile Devices group are included as an "Add" step in the Selection Steps pane. To reuse a group or calculated item from the Catalog pane: 1. On the Results tab, display an analysis containing the same column to which you want to apply the selections from a group or calculated item. 2. In the Catalog pane, select the group or calculated item. 3. On the toolbar of the Catalog pane, click Add More Options. 4. Select Add to add the group or calculated item itself. Select Add Members to add only the group or calculated item members. 8-20 Using Oracle Business Intelligence Cloud Service

Manipulating Members Using Groups and Calculated Items To reuse a group or calculated item from the Edit Member Step dialog: 1. On the Results tab, display an analysis containing the same column to which you want to apply the selections from a group or calculated item. 2. Display the Selection Steps pane. 3. In the entry for the column you want, click the pencil icon. The Edit Member Step dialog is displayed. 4. From the Action menu, select Start with Group or Calculated Item. 5. Move the saved group or calculated item from the Available area to the Selected area. 6. Click OK. To reuse a group or calculated item from the Selection Steps pane: 1. On the Results tab, display an analysis containing the same column to which you want to apply the selections from a group or calculated item. 2. On the Selection Steps pane select Then, New Step for the appropriate column. 3. Select Add Groups or Calculated Items. 4. Select Select Existing Groups and Calculated Items. 5. On the resulting dialog, select the group or calculated item from the Available area and move it to the Selected area. 6. Click OK. Deleting Groups and Calculated Items You can delete inline and named groups and calculated items. For example, suppose you no longer need the combination of Flip Phones and Smart Phones in the analysis. You can delete the Mobile Devices group. To delete an inline group or calculated item: 1. On the Analysis Editor: Results tab, right-click on the cell that contains the group or calculated item that you want to delete. 2. Click Remove. To delete a named group or calculated item: 1. On the global toolbar, click Catalog. 2. Locate the group or calculated item in the Catalog page. Filtering and Selecting Data for Analyses 8-21

Manipulating Members Using Groups and Calculated Items 3. Click More on the group or calculated item. 4. Select Delete. 8-22 Using Oracle Business Intelligence Cloud Service

9 Prompting in Analyses and Dashboards This topic describes how to create prompts for soliciting values to display in analyses and dashboards. Topics: Typical Workflow for Prompting in Analyses and Dashboards Creating Prompts Editing Column Prompts Adding Prompts to Dashboard Pages Typical Workflow for Prompting in Analyses and Dashboards Here are the common tasks to start creating prompts for soliciting values to display in analyses and dashboards. Tasks Description More Information Create an analysis Create a column prompt Edit a prompt Add a column prompt to a dashboard page Select and arrange columns that you want to use in an analysis. Create a prompt to filter the data that you see displayed. Edit the prompt to change it in every place where it is used. Add a prompt to a new or existing dashboard. Creating Your First Analysis Creating Column Prompts Editing Column Prompts Adding Prompts to Dashboard Pages Creating Prompts You can create column prompts and variable prompts. You can also override a selection step with a prompt. Topics: Creating Column Prompts Creating Variable Prompts Overriding a Selection Step with a Prompt Prompting in Analyses and Dashboards 9-1

Creating Prompts Creating Column Prompts A prompt enables you to filter the data that you see. A column prompt enables users viewing a dashboard to select a value for a column that affects what they see on the dashboard. Video Tutorial Use the following procedure to create: A named column prompt that you can apply to one or more dashboards. For information, see Adding Prompts to Dashboard Pages. An inline column prompt that is embedded in an analysis. For example, you can add a prompt to the Brand Revenue analysis so that the analysis can be reviewed for specific brands. You add a prompt directly to a column in the analysis (an inline prompt). To create a column prompt: 1. Open the analysis for editing. 2. On the Definition pane of the Prompts tab, click New to access the prompt type selection list. Select Column Prompt and select the appropriate column. 3. (Optional) Click Edit Formula to modify the column formula. For information, see Editing the Formula for a Column. Suppose that you added a SQL case statement to the analysis' column instance and you want to use that CASE statement within the prompt. You must specify the same SQL CASE statement in the prompt's column formula. 4. In the Label field, change the default label by entering a caption for the column filter prompt. The caption displays as the field label for the prompt. For example, "Select a currency." 5. In the Description field, enter a short description for the prompt. This description becomes tooltip text, which is displayed when the user hovers the mouse pointer over the prompt's label in the dashboard or analysis. 6. From the Operator list, select the operator to use, such as "is greater than." If you want the user to select the operator at runtime, then select the *Prompt User operator. If you are creating a prompt that includes a group in the prompt's value selection list, then you must set the Operator to either is equal to/is in or is not equal to/is not in. For more information about groups, see About Groups and Calculated Items. 7. In the User Input field, select how you want the prompt interface to ask the user for input. For example, prompt the user with a radio button to select only one prompt value. 9-2 Using Oracle Business Intelligence Cloud Service

Creating Prompts 8. Depending on the type of user input that you specified, enter the appropriate values in the User Input field. For example, select Custom Values to indicate that users can select from a list of prompt values that you created rather than the values supplied by the column. 9. Within the Options section, select prompt options to specify the display of list values and user interaction with the prompt. The prompt options vary depending on the user input type and list values type that you selected. 10. In the Default selection field, select the prompt value or values that users see initially. If you select a default type, then a field is displayed where you can either select specific values, or specify how you want the default values to be determined. For example, if you select SQL Results, you must then supply a SQL statement to generate the list of values. 11. Click OK. The new prompt is displayed in the Definition pane. 12. Click Save Prompt in the editor or save the analysis. 13. Use the arrow buttons in the Definition pane to reorder the selected prompt. Reordering the prompts controls the order in which the choices are displayed to users at runtime. 14. Select the type of layout you want on the prompts page by clicking New Row or New Column in the Definition pane. A row-based layout saves space because it organizes prompts horizontally. A column-based layout aligns prompts into neat columns. Click the boxes in the New Column or New Row column in the Definition table that correspond to where you want to add a new column or row to the prompts page. Prompting in Analyses and Dashboards 9-3

Creating Prompts Creating Variable Prompts 15. Preview the prompt with sample data using the Display pane, or click Preview (if available) in the Definition pane toolbar to view the prompt with actual prompt values. For information on using column prompts with dashboards, see Adding Prompts to Dashboard Pages. A variable prompt enables the user to select a value that is specified in the variable prompt to display on the dashboard. A variable prompt is not dependent upon a column, but can still use a column. You can use variable prompts to enable the user to specify existing data to perform sales projections. For example, you can create a variable prompt called Sales Projections and specify the variable prompt values as 10, 20, and 30 percent. Then you create an analysis that contains the Region and Dollars columns. Within the Dollars column formula, you select the multiply operator and insert the Sales Projection variable. When users run this analysis, they can select a percentage by which to recalculate the Dollars column. To create a variable prompt: 1. Open the analysis for editing. 2. Display the Prompts tab. 3. On the Definition pane of the Prompts tab, click New then Variable Prompt to display the New Prompt dialog. 4. In the Prompt for field, select the variable type that you are creating and then enter the name of the variable. This variable name is the name that you add to the analysis or dashboard where you want the variable prompt's value specified by the user to display. Currently, you can create only presentation variables. 5. In the Label field, enter a caption for the variable filter prompt. The caption is displayed as the prompt's field label. 6. In the Description field, enter a short description for the prompt. This description is displayed as tooltip text, which is displayed when the user hovers the mouse pointer over the prompt's label in the dashboard or analysis. 7. In the User Input field, select how you want the prompt interface to ask the user for input. For example, prompt the user with a radio button to select only one prompt value. 9-4 Using Oracle Business Intelligence Cloud Service

Creating Prompts 8. If you selected either the Choice List, Check boxes, Radio buttons, and List box user input type, then you must also specify the prompt's list of values. 9. Within the Options section, select the prompt options. The prompt options vary depending on the user input type that you selected. The prompt options enable you to further specify how you want the user to interact with the prompt. For example, whether user input is required. 10. In the Default selection field, select the prompt value that users see initially. If you select a specific value, then the Default Value field is displayed in which you can enter a value. 11. Click OK to display the prompt is displayed in the Definition pane. 12. Save your changes. Overriding a Selection Step with a Prompt You can override a selection step with either a dashboard prompt or an inline prompt. For example, you can specify that the Products.Brand selection step be overridden with a column prompt specifying the BizTech and FunPod members. To allow a selection step to be overridden by a column prompt: 1. Open the analysis for editing. 2. After you have specified the columns for the analysis, navigate to the Selection Steps pane by selecting Show/Hide Selection Steps Pane. 3. Specify the selection steps for the analysis. 4. Determine which selection step you want to override with a column prompt and click Edit. The appropriate Edit Step dialog is displayed. 5. In the dialog, select Override with prompt, if it is available for that type of step. 6. Click OK and save the analysis. Prompting in Analyses and Dashboards 9-5

Editing Column Prompts Editing Column Prompts You can edit a saved dashboard prompt or inline prompt, to propagate its changes to wherever the prompt is used. For example, you can edit the prompt for the Brand column to change the user input to a choice list. This change is propagated to the Brand Revenue analysis where the prompt is used. To edit a prompt: 1. In the Definition pane on the Prompts tab, double-click to open the appropriate prompt. 2. Make the appropriate changes in the Edit Prompt window. For example, change the label for the prompt or change the user input to a choice list. 3. Click OK. 4. Click Save Prompt. The changes are propagated to wherever the prompt is used. Adding Prompts to Dashboard Pages You can add a prompt to a dashboard or dashboard page. Video For example, you can create a dashboard prompt for the Brand column. You add the prompt to the Sales Performance dashboard, to drive the content on the dashboard page. You add a filter for Brand that uses the "is prompted" operator to flag the column as ready to be filtered by a prompt. When the prompt is used, the results include only records where the data in the column that is prompted matches the user's choices. For more information, see About Prompted Filters. To add a dashboard prompt to a dashboard page: 1. Open the dashboard for editing. 2. In the Dashboard builder's Catalog pane, locate and drag and drop an object such as an analysis onto a section in the dashboard page. 9-6 Using Oracle Business Intelligence Cloud Service

Adding Prompts to Dashboard Pages 3. In the Dashboard builder's Catalog pane, locate and drag and drop the dashboard prompt onto a section in the dashboard page. The dashboard prompt is added to the dashboard page. 4. To specify whether to include the prompt's Apply and Reset buttons on the dashboard page, in the toolbar of the Dashboard builder, click Tools. Then select Prompts Buttons on Current Page and either Apply Buttons or Reset Buttons, and one of the following options: Option Use Prompt Setting Show All Apply Buttons or Show All Reset Buttons Hide All Apply Buttons or Hide All Reset Buttons Description Uses the buttons as specified in the Prompt definition in the Prompt editor. Shows the buttons for the prompts. Hides the buttons for the prompts. Note: These options apply to the dashboard page and override the settings for the Apply and Reset buttons for the prompt definition and dashboard properties with one exception. The settings are not overridden if the Prompts Apply Button and Prompts Reset Button fields on the Dashboard Properties dialog are set to Use page settings. 5. Click Save in the dashboard toolbar. 6. To preview the dashboard page, click Preview in the dashboard toolbar. Prompting in Analyses and Dashboards 9-7

10 Making Analyses Interactive This topic describes how you can make analyses and dashboards more interactive by linking to other content. Topics: Typical Workflow for Making Analyses Interactive Creating Named Actions for Reuse Creating Inline Actions Adding Actions to Analyses Adding Actions to Dashboard Pages Editing Named Actions Editing and Deleting Actions and Action Links Added to Analyses Editing Actions Action Links and Action Link Menus Added to Dashboard Pages Saving Inline Actions in Analyses to the Catalog Saving Inline Actions in Dashboards to the Catalog Typical Workflow for Making Analyses Interactive Here are the common tasks to start making analyses more interactive. Task Description More Information Create an analysis Create a named action Create an inline action Add an action to an analysis Add an action to a dashboard Select and arrange columns that you want to use in an analysis. Create an action and save it to the catalog. Create an action and save it with an analysis. Add an action to a column value in an analysis. Add an action or an action menu to a dashboard. Creating Analyses Creating Named Actions for Reuse Creating Inline Actions Adding Actions to Analyses Adding Actions to Dashboard Pages Making Analyses Interactive 10-1

Creating Named Actions for Reuse Creating Named Actions for Reuse You can create an action that enables end users to navigate to related content and to web pages. You can include actions alongside data in an analysis and on dashboard pages so that you can easily link to other BI content and web pages. Users run an action by clicking an action link that is embedded within an analysis on column headings and column values. Users can also click links in views such as graphs, and on grand totals within tables and pivot tables. For more information, see Adding Actions to Analyses, Adding Actions to Dashboard Pages, and Adding Interactivity to Analyses. You create a named action so that you can save it in the catalog and reuse it. For example, you can create a named action called Navigate to Company Home. This action displays your company's home page. By saving this action in the catalog, you enable the action to be included on pages in multiple dashboards. To create a named action: 1. In the global header, click New, then select Action. 2. Select the type of action to create. You can navigate either to BI Content or to a web page using a URL. If you navigate to BI content, then the action that you create might display a graph of company revenue for selected brands. You can instead navigate to a web page, such as the home page of your company's web site. 3. Specify the navigation content. To navigate to BI Content, select an analysis or dashboard. To navigate to a web page, specify the URL of the page in the URL field. 4. (Optional) To embed a parameter value within the URL, click Define Parameters to display the Define Parameters list. 5. Click Add Parameter. 6. Specify the column values for the parameter. For example, you can embed a parameter value anywhere within the URL for a Navigate to a Web Page action. Enter the @{Name} value, where "Name" is the value specified in the Name column. You can embed any number of parameters. 10-2 Using Oracle Business Intelligence Cloud Service

Creating Named Actions for Reuse You can define parameters that are fixed, hidden, or optional. Type Fixed Hidden Optional Description A fixed parameter can be seen, but its value cannot be set by a user. A hidden parameter cannot be seen and its value cannot be set by a user. (Note that hidden does not mean that the parameter is secure.) An optional parameter does not require a value in order for the action to be run. Note: For actions that navigate to BI Content, parameters are automatically passed from the source to the target. When navigating from one analysis to another, if the source row of data contains a field with the same logical name as a field used in a filter on the target analysis, then the value of this field is passed as a parameter. Set the operator on the filter to is prompted or is equal to / is in. 7. (optional) Click Options to display the Action Options dialog where you customize the information that is displayed when the action runs. 8. Specify the customization that you want, for example: Customization Action Help Text Link URL Description Specify the text of the dialog that is displayed to supply action parameter values. To embed a URL link within the text, use the token @{URL}. The URL link is substituted for the token. Specify to display a URL link below or within the text of the dialog to supply action parameter values. For example, you can display a link that navigates to a URL that provides more information about an action being run. If you embed the @{URL} token in the text, then the URL (or URL label, if provided) is displayed within the text. If you do not embed Making Analyses Interactive 10-3

Creating Inline Actions Customization Description the token in the text, then the URL (or URL label, if provided) is displayed beneath the text. 9. Click OK. 10. Click Save Action. 11. Specify the information for saving the action. 12. Verify that the action runs properly with these steps: a. Navigate to the named action in the catalog. b. Click Execute. c. Respond to any request for more information or any confirmation prompt that is displayed. Creating Inline Actions An inline action is an action that you define at the point of use and do not save by name in the catalog. Instead, you save the action as part of an analysis or dashboard page. For example, in the Brand Revenue analysis, you can include an inline action that contains an action link to an Opportunity Detail web site. You create an inline action when you: Create an analysis and add a new action to a column heading, column value, or hierarchy level value using an action link. For information, see Adding Actions to Analyses. Edit a dashboard page and add a new action to the page using an action link or an action link menu. For information, see Adding Actions to Dashboard Pages. Adding Actions to Analyses You can use an action link to add actions to a column heading, column value, or hierarchy level value in an analysis. For example, you can edit the Brand Revenue analysis to add an action that features an action link. This link can enable sales consultants to navigate to an Opportunity Detail web site. The consultants can query the site for an opportunity by responding to a prompt for Opportunity Name or Opportunity ID. To add an action to an analysis: 1. Open the analysis for editing. 2. On the Criteria tab, move the mouse pointer over the Options menu for a column and select Column Properties. 10-4 Using Oracle Business Intelligence Cloud Service

Adding Actions to Analyses 3. Click the Interaction tab in the Column Properties dialog. 4. In the Primary Interaction box in the Column Heading area or the Value area, select Action Links to display the Action Links area. 5. To add a new action: If actions have been saved as systemwide defaults for the column or level, then click Add Action Link and select New Action Link. If no actions have been saved as systemwide defaults for the column or level, then click Add Action Link. The New Action Link dialog is displayed. 6. In the Link Text field, enter the text to display as the link to run the associated action. 7. Create or add the action as follows: To create an inline action, click Create New Action, select the type of action, and specify the settings for the action. To add a named action, click Select existing action and complete the Select Action dialog. Specify any associated parameters in the Edit Parameter Mapping dialog. 8. Click OK in the New Action Link dialog to add the action link to the Action Links area in the Interaction tab. 9. For each additional action link, repeat the previous steps. 10. Optionally select Do not display in a popup if only one action link is available at runtime. When only one action link is available at runtime, the action link is run immediately rather than being displayed in a menu for selection. 11. Select Enable on Totals when three things are true. The analysis contains a total or grand total. The associated column contains an action link. You want the action link to be applied to both the column and the total or grand total. This option does not apply to column heading action links and by default, this behavior is turned off. 12. Click OK to close the Column Properties dialog and save the analysis. Making Analyses Interactive 10-5

Adding Actions to Dashboard Pages Adding Actions to Dashboard Pages You can add actions to dashboard pages using action links and action link menus. Topics Adding Actions to Dashboard Pages Using Action Links Adding Actions to Dashboard Pages Using Action Link Menus Adding Actions to Dashboard Pages Using Action Links You can add actions to dashboard pages by adding to a section on the dashboard page an Action Link object to which you add an action. For a dashboard page that contains one or more action links, users can click a link to run the associated action. For example, you can edit the Sales Performance dashboard page to add an action that features an action link. This link navigates to an external Opportunity Detail web site. The consultants can query the site for an opportunity by responding to a prompt for Opportunity Name or Opportunity ID. To add an action to a dashboard page using an action link: 1. Open the dashboard page for editing. 2. From the Dashboard Objects pane, drag and drop an Action Link object on the dashboard page. 3. Click Properties for the Action Link object to display the Action Link Properties dialog. 4. Complete the fields in the dialog, for example: Field Open Link in New Window Description Select this option to open the link in a new browser window or tab. Deselect this option to open the link in the same browser window or tab. For a named action for this action link, the default value for this component is determined by the definition of the named action. That is, by the value specified for the Open In New Window component in the Action Options dialog: Invoke Action tab. You can override this default value. The value that you set here ultimately determines whether to open the link in a new window or new tab. 10-6 Using Oracle Business Intelligence Cloud Service

Adding Actions to Dashboard Pages Field Add to Briefing Book Description Select this option to enable the action that is associated with the action link to be run in a briefing book. The number of briefing book navigation links to be followed must be greater than 0. A briefing book icon is displayed to the left of the action link on the dashboard page and in the briefing book. The icon indicates that you can run the action. You can set the number of briefing book navigation links to be followed. Use the Save Briefing Book Content dialog or in the Page Properties dialog. Deselect this option to prevent the action from being run in a briefing book. See Organizing Dashboard Pages in Briefing Books. 5. Click OK in the Action Link Properties dialog. 6. Click Save on the Dashboard builder to save the dashboard page. Adding Actions to Dashboard Pages Using Action Link Menus You can add actions to dashboard pages by adding an action link menu object to a section on a page. You add action links to the action link menu object. For a dashboard page that contains an action link menu, users can select from the action link menu to run the action. For example, you can add an action link menu to a page in the Sales Performance dashboard. This menu can enable sales consultants to navigate to either an external Opportunity Detail web site or to an internal Brand Revenue dashboard page. To add an action to a dashboard page using an action link menu: 1. Open the dashboard for editing. 2. From the Dashboard Objects pane, drag and drop an Action Link Menu object on the dashboard page. 3. Click Properties for the Action Link Menu object to display the Action Link Menu Properties dialog. 4. Add the action links to the menu: Goal Add an action link that already exists on the page Procedure Drag and drop the existing Action Link object onto the Action Link Menu object. Making Analyses Interactive 10-7

Editing Named Actions Goal Add a new action link. Reorder the list of action links and change the order of how they are displayed on the action link menu. Procedure Click Add to display the Action Link Properties dialog and complete the dialog. Use the arrows to the right of the list. 5. Click OK in the Action Link Menu Properties dialog. 6. On the Dashboard builder, click Save to save the dashboard page. Editing Named Actions You can edit an existing named action. For example, you can edit the Navigate to Brand Revenue action in the Sales Performance dashboard to navigate to a newly created analysis. To edit a named action: 1. Navigate to the action in the catalog. 2. Click Edit to display the Edit Action dialog. 3. Edit the action and click OK. 4. Click Save Action. Note: You delete a named action in the same way that you delete any object in the catalog. Navigate to the action in the catalog, click More and select Delete. Editing and Deleting Actions and Action Links Added to Analyses You use action links as hot links that run actions. For example, you can create an action link called "Navigate to Brand Revenue." This link runs an action that navigates to an analysis that shows revenue figures in tables and graphs. To edit an action and action link that have been added to an analysis: 1. Open the analysis for editing. 2. On the Criteria tab, move the mouse pointer over the Options menu for a column and select Column Properties. 10-8 Using Oracle Business Intelligence Cloud Service

Editing Actions, Action Links, and Action Link Menus Added to Dashboard Pages 3. Click the Interaction tab in the Column Properties dialog. 4. In the Action Links area, select the action to edit and click Edit Action Link to display the Edit Action Link dialog. 5. Make the appropriate changes to the action link. 6. Click More and select Edit Action. 7. Edit the action in the Edit Action dialog and click OK to close the dialogs. 8. Click Save Analysis in the Criteria tab of the Analysis editor. You can delete an inline action. For example, you can delete an action link that navigates to an obsolete analysis that shows revenue figures in tables and graphs. 1. Open the analysis for editing. 2. On the Criteria tab, move the mouse pointer over the Options menu for a column and select Column Properties. 3. Click the Interaction tab in the Column Properties dialog. 4. In the Action Links area, select the action link that you want to delete. 5. Click Delete. 6. Click OK in the Column Properties dialog. Editing Actions, Action Links, and Action Link Menus Added to Dashboard Pages You can edit actions, action links, and action link menus that you have added to dashboard pages. For example, you can edit an action in the Sales Performance dashboard that navigates to an updated URL for an Opportunity Detail site. Making Analyses Interactive 10-9

Saving Inline Actions in Analyses to the Catalog To edit an action, action link, or action link menu that has been added to a dashboard page: 1. Open the dashboard for editing. 2. If the action and action link are associated with an action link menu: a. Click Properties for the Action Link Menu object to display the properties dialog. b. Make the appropriate changes to the menu label and caption. c. In the Action Links area, select the action to edit and click Edit. 3. If the action and action link are standalone, then click Properties for the Action Link object to which the action is associated. The properties dialog is displayed. 4. Make the appropriate changes to the action link. 5. Click More and select Edit Action to display the Edit Action dialog. 6. Edit the action and click OK. 7. Click OK in the Action Link Properties dialog, and in the Action Link Menu Properties dialog (if displayed). 8. Click Save to save the dashboard. Note: You can delete action links and action link menus that you have added to dashboard pages. Open the dashboard for editing and click Delete on the Action Link or Action Link Menu toolbar. Saving Inline Actions in Analyses to the Catalog You can select an inline action in an analysis to be saved in the catalog. For example, in the Brand Revenue analysis, you can save an inline action in the catalog. When you save the action to the catalog, you can include it in other analyses and dashboard pages in the Sales Performance dashboard. To save an inline action in an analysis: 1. Open the analysis for editing. 2. On the Criteria tab, move the mouse pointer over the Options menu for a column and select Column Properties. 10-10 Using Oracle Business Intelligence Cloud Service

Saving Inline Actions in Dashboards to the Catalog 3. Click the Interaction tab in the Column Properties dialog. 4. In the Action Links area, select the action to save and click Edit Action Link. The Edit Action Link dialog is displayed. 5. Click More and select Save Action As to display the dialog to specify the save criteria. 6. Specify the save criteria and click OK. 7. Click OK in the Edit Action Link dialog. 8. Click OK in the Column Properties dialog. Saving Inline Actions in Dashboards to the Catalog You can select an inline action in a dashboard to be saved into the catalog. For example, in the Sales Performance dashboard, you can save an inline action in the catalog. When you save the action to the catalog, you can include it in the Brand Revenue analysis, which is not included in the dashboard. To save an inline action in a dashboard to the catalog: 1. Open the dashboard for editing. 2. If the action and action link are associated with an action link menu: a. Click Properties for the Action Link Menu object to display the properties dialog. b. Make the appropriate changes to the menu label and caption. c. In the Action Links area, select the action to edit and click Edit. 3. If the action and action link are standalone, then click Properties for the Action Link object to which the action is associated. The properties dialog is displayed. 4. Click More and select Save Action As to display the dialog to specify the save criteria. Making Analyses Interactive 10-11

Saving Inline Actions in Dashboards to the Catalog 5. Specify the save criteria and click OK. 6. Click OK in the Action Link Properties dialog, and in the Action Link Menu Properties dialog (if displayed). 7. Click Save to save the dashboard. 10-12 Using Oracle Business Intelligence Cloud Service

11 Managing Content This topic describes how to manage your content in the catalog. Typical Workflow for Managing Content Renaming Objects Accessing Favorites Easily Accessing Properties Sharing Your Content with Others Assigning Ownership Taking Ownership Typical Workflow for Managing Content Here are some common tasks that you perform to access and organize content in the catalog. Task Description For More Information Find and explore your content Rename content View or set content properties Share your content with others Change content ownership Exploring your content, including searching for items that you need to edit. Improve or update the naming of your content. Display information about your content or change various content options and properties. Assign permissions so that you can share your content with others. Assign another user as the content owner. Finding and Exploring Your Content Renaming Content Accessing Properties Sharing Your Content with Others Assigning Ownership Renaming Content You can rename items and views to make their names more meaningful to you. Topics: Renaming Items Renaming Views Managing Content 11-1

Accessing Favorites Easily Renaming Items Renaming Views You can rename items to make their names more meaningful to you. For example, you can change the name of the "High Products" filter to "Top 3 Products." To rename items: 1. In the global header, click Catalog. 2. In the Catalog page, search for the item that you want to rename, and give it a new name. For more information, see Finding and Exploring Your Content. 3. Optionally click Preserve references to the old name of the item, if the option is available for the item. Use this option to specify that existing references to the previous name of the item are maintained. This creates a shortcut with the old name that points to the renamed item in the catalog. If you do not select this option, then existing references break. 4. Click OK. You can rename views to make their names more meaningful to you. For example, you can change the name of a view from "Sales Forecast 2014" to "Forecast 2014." To rename a view: 1. Open the analysis for editing. 2. On the Results tab, click Edit View. 3. In the view editor toolbar, click Rename View. 4. In the Rename View dialog, give the view a new name. 5. Click OK. Accessing Favorites Easily You can access favorites easily. Video Tutorial Adding Favorites Topics: Adding Favorites Removing Favorites You can bookmark as favorites the content that you work with the most. Your favorites are displayed with a gold star n the catalog. For example, you might regularly view the Loyal Customers analysis. You can flag the analysis as a favorite to help you quickly access it whenever you need it. 11-2 Using Oracle Business Intelligence Cloud Service

Accessing Properties To add favorites: 1. In the global header, click Catalog. 2. In the Catalog page, search for the item that you want to mark as a favorite. For more information, see Finding and Exploring Your Content. 3. Click More, then click Add to Favorites. Note: You can also add an item to your favorites list while you are viewing or editing it. Open the item in its designated viewer or editor. Then, in the global header, hover the mouse pointer over Favorites and click Add to Favorites. Removing Favorites You can remove items from your favorites list that you no longer need to access as often. For example, you can remove the previous year's Loyal Customers analysis from your favorites list because it is now out-of-date. To remove favorites: 1. In the global header, click Catalog. 2. In the Catalog page, search for the favorite to remove. For more information, see Finding and Exploring Your Content. 3. Click More, then click Remove from Favorites. Note: You can also remove items from your favorites list in these ways: Opening or editing an item. In the global header, hover the mouse pointer over Favorites and click Remove from Favorites. Using the Manage Favorites dialog. In the global header, click the Favorites menu, click Manage Favorites, select the object, click Delete and OK. Accessing Properties Administrators can access the properties of any item or folder to perform tasks such as view system information or change access levels. All other users can access and modify the properties for only those items that they create or own. For example, you might want to change the Brand Revenue analysis to be read-only so that other users can t modify it. To access properties: 1. In the global header, click Catalog. 2. In the Catalog page, search for the item to which you want to access properties. For more information, see Finding and Exploring Your Content. Managing Content 11-3

Sharing Your Content with Others 3. In the Folders pane, select an item or folder. 4. Below the document, click More and then Properties, or click Properties in the Tasks pane. 5. Review or change the settings in the Properties dialog. For example, you can set an item as read-only. For more information about taking ownership of an item, then see Assuming Ownership. 6. Click OK. Sharing Your Content with Others You can give others access to items in the catalog and to dashboard sections. This helps you to control the content that users can view or edit. Tutorial Sharing Items Topics: Sharing Items Sharing Dashboard Sections To share items with other users, you must give them the appropriate permissions to access the items. The permissions that you can assign to others vary depending on the type of content. To change permissions, you must have the Change Permission privilege. For example, you might want to grant the Change Permission privilege to another sales consultant. This enables the user to assign permissions to the Sales Forecast analysis. To share an item with another user: 1. In the global header, click Catalog. 2. In the Catalog page, search for the item to which you want to assign permissions. 11-4 Using Oracle Business Intelligence Cloud Service

Sharing Your Content with Others For more information, see Finding and Exploring Your Content. 3. Go to the Catalog area and locate an item or folder. 4. Select More and then Permissions, or go to the Tasks pane and click Permissions. The Permissions dialog is displayed. 5. In the Permission dialog, click Add users/roles to access the Add Application Roles and Users dialog to add any required accounts. The roles and users inherit permissions from the roles of which they are members. For example, you can grant Full Control permission to the BIServiceAdministrator application role on the Sales Revenue analysis. This enables any user or application role with that role to have Full Control on the item. You can see the permissions that users and roles have on items (either granted directly or inherited). Click the Click to see effective permissions button in the Add Application Roles and Users dialog. 6. In the Permissions dialog, click the Permissions list. Most of the items in the list are parent permissions and contain several child permissions. 7. Optionally, to build a specific list of permissions, click Custom. This option gives the user authority to bypass any permissions set on the folder that prevent the user from accessing the item from the Catalog or a dashboard. This option does not change the folder permissions. For example, you can grant users the Traverse permission for the /Company Shared/Test folder. Then, they can access items embedded in dashboards stored in the /Company Shared/Test folder. Also, they can access embedded items in dashboards stored in sub-folders, such as /Company Shared/Test/Guest folder. However, users cannot access (meaning view, expand, or browse) the folder and sub-folders from the Catalog. 8. Click OK twice. Managing Content 11-5

Assigning Ownership of Items Sharing Dashboard Sections You can give others access to dashboard sections, thereby controlling which users have access to those sections. To grant access, you assign permissions to users of the dashboard. For example, you assign permissions for the Project Costs section of the dashboard to the BI administrator. You can restrict access to BI consumers to prevent unwanted changes. To assign dashboard section permissions to another user: 1. Open a dashboard for editing. 2. Select Properties in the section toolbar. 3. Select Permissions. 4. In the Permissions dialog, click the Permissions list to select permissions. 5. Click OK. Assigning Ownership of Items When you create catalog items, you can grant ownership of those items to others. Also, a user who has been granted the proper privileges can take ownership of an item. For example, you can create a Brand Revenue analysis and grant ownership to a Regional Sales Analyst tasked with maintaining the analysis going forward. To assign item ownership to others: 1. In the global header, click Catalog. 2. In the Catalog page, search for the item to which you want to assign ownership. For more information, see Finding and Exploring Your Content. 3. Go to the Catalog area and find the item or folder. 4. Select More and then Permissions, or go to the Tasks pane and click Permissions 5. In the Permissions table, click the Owner column to specify the new owner. 6. Click OK. 11-6 Using Oracle Business Intelligence Cloud Service

Assuming Ownership of Items Assuming Ownership of Items As a user or a member of a role, you can take ownership of shared folder items if you are assigned the BIServiceAdministrator role. For example, if you are a user of the Sales group, you can assign properties to the Sales Forecast analysis to mark yourself as an owner. To take ownership of a shared folder item: 1. In the global header, click Catalog. 2. In the Catalog page, search for an item that you want to own. For more information, see Finding and Exploring Your Content. 3. Go to the Catalog area and locate an item or folder. 4. Select More and then Properties, or go to the Tasks pane and click Properties to display the Properties dialog. 5. In the Ownership area, select whether to take ownership of just the item or of the item and its child items. 6. Click OK. Managing Content 11-7

Part IV Loading Data in Oracle Business Intelligence Cloud Service This part explains how to load data that you want to model using Oracle Business Intelligence Cloud Service. Chapters: Getting Your Data to the Cloud Loading Data from Files Loading Data from Relational Tables Automating Loading Data Using Programmatic Methods

12 Getting Your Data to the Cloud This topic describes how to get data into the cloud database integrated with Oracle BI Cloud Service so you can start modeling the data. Topics: Uploading Your Data to the Cloud Uploading Your Data to the Cloud Oracle BI Cloud Service requires you to upload your data to an Oracle Database Cloud Service before you can start to build a data model from which you can create analyses and dashboards. Oracle BI Cloud Service can integrate with Oracle Database Cloud Service (Database Schema) or Oracle Database Cloud Service (Database as a Service). See How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service? Oracle BI Cloud Service provides simple tools to upload files and relational tables, as well as automated mechanisms for data movement to the cloud. You can: Directly load your data from files using a web-based data loader available in Oracle BI Cloud Service See Loading Data from Files. Load data from relational tables (for example, an Oracle database) See Loading Data from Relational Tables. Use programmatic methods to automate data loading from on-premises and cloud sources See Automating Loading Data Using Programmatic Methods. This topic describes different ways to load data that you want to model. If you have some data you want to upload for ad-hoc analysis, see Adding Your Own Data. Getting Your Data to the Cloud 12-1

13 Loading Data from Files You can load data from text files (TXT and CSV) and Microsoft Excel spreadsheets (XLS and XLSX) into the Oracle Database Cloud Service (Database Schema) included with Oracle BI Cloud Service. Topics Typical Workflow for Loading Files About Data Loader About Column Types Transforming Your Data Loading Your Files into a New Table Loading Your Files into an Existing Table Viewing Data Load History Correcting Errors in Data Loads Typical Workflow for Loading Files Here are the common tasks to load files: Task Description More Information Load files into a new table. Load files into an existing table. View reports of previous data loads. View and correct errors that occurred in past data loads. Use Data Loader to load files from an external source into a new table on Oracle Database Cloud Service (Database Schema). Use Data Loader to load files into an existing table, to add new records, or to overwrite previously uploaded values. View the results of previous attempts to load files with Data Loader. View and fix errors that were reported from previous data loads. Loading Your Files into a New Table Loading Your Files into an Existing Table Viewing Data Load History Correcting Errors in Data Loads About Data Loader Data Loader is an easy-to-use browser-based tool for loading text files (TXT and CSV) and Microsoft Excel spreadsheets (XLS and XLSX) into the Oracle Database Cloud Service (Database Schema) included with Oracle BI Cloud Service. You don t need the Loading Data from Files 13-1

About Column Types assistance of a database administrator to load data files because Data Loader is wizard-driven and intuitive. Note: Data Loader loads data to Oracle Database Cloud Service (Database Schema). If your Oracle BI Cloud Service is connected to Oracle Database Cloud Service (Database as a Service), see Loading Data from Relational Tables and Automating Loading Data Using Programmatic Methods. Use Data Loader to perform a full manual refresh, increment manual data loading, upsert (insert and update) data into existing tables, and add data to your model. You can: Load moderate amounts of data from sources, such as Microsoft Excel spreadsheets, into destination tables on Oracle Database Cloud Service (Database Schema), so that you can include the data in analyses and dashboards. Perform simple data transformations. Map columns. Correct load errors. Data Loader can handle input files of up to 500,000 rows. After loading data, use Data Modeler to model your business data for analyses and dashboards. As a guideline, use SQL Developer for input files exceeding 500,000 rows. You view and download SQL Developer and corresponding documentation on Oracle Technology Network (OTN). In addition to Data Loader, there are other ways that you can upload data. See Loading Data from Relational Tables and Automating Loading Data Using Programmatic Methods for more information. About Column Types Data that you upload to Oracle BI Cloud Service through Data Loader is stored as either a number, date, or character, and is in UTF-8 character encoding. Column Type Description Notes NUMBER TIMESTAMP Stores only numbers of the following characters: numbers from 0-9, the period, and the dash. Stores dates in different formats, depending on the regional configuration of the underlying database. You can optionally specify the column length and number of decimal places. If you specify decimal places without specifying column length, then you can specify an asterisk (*). The asterisk indicates that the column length is obtained from the underlying database. If the type is TIMESTAMP, you can t specify a column length or number of decimal places. VARCHAR2 Stores a character string. You must specify a column length if the column type is VARCHAR2. Supported lengths for character strings are 4000 for Oracle Database 11g and up to 32767 for Oracle Database 12c, depending on the database configuration. 13-2 Using Oracle Business Intelligence Cloud Service

Transforming Your Data Transforming Your Data When you upload data to Oracle Database Cloud Service (Database Schema) using Data Loader you can use transformations to normalize the content of the data. Several types of transformations are available: Transformation Type Uppercase Lowercase Trim spaces Format as a number Description Converts every character in the data column to upper case. Converts every character in the data column to lower case. Deletes trailing spaces in the data column. For example, "ABC " is trimmed to "ABC" in the data column. Preserves specific characters in the string. These characters include numbers from 0 through 9, a period, and a dash. For example, the string "$-1,000.00" is transformed into "-1000.00", which is a valid column of type NUMBER in the table. Loading Your Files into a New Table You can load your files into a new table on Oracle Database Cloud Service (Database Schema). For example, you might want to upload a denormalized file that contains fact and dimensional data that you want to use in your data model. Video To load data into a new table using Data Loader: 1. Sign in to Oracle BI Cloud Service. 2. On the Home page, click Load Data. 3. In Data Loader, click the Load Data button. 4. Use the Select Data page to specify the data to load into the database. Click Upload to select a file from which to upload data, and then click Open. Alternatively, you can copy the data from another source and paste it into the preview pane on the page. The data loads into the pane and becomes read-only. If the results aren t what you expected to see in the preview pane, click Clear to remove pasted or uploaded text, and then try again. 5. Optionally, specify the following on the Select Data page: Field or Element Ignore the first number lines Description Enter the number of first rows to skip during loading. For example, you might want to skip rows that are related to the title of the file. Loading Data from Files 13-3

Loading Your Files into a New Table Field or Element The first line contains header names Delimiter Description Select this option to indicate that the first row of data to load contains header names. The first row of data is the one after the number of rows that you specified to skip. Select the type of delimiter that is used to separate the data in your file. The delimiter can be a Comma, Pipe, or Tab. 6. Click Next. 7. On the Select Destination page, select New Table, and then name the table. Data Loader analyzes the data and suggests data types, lengths, and column names for the new table. Data Loader also provides a proposed mapping of the first row, the destination table, and the uploaded data. Review the proposed mapping, and then optionally apply the following changes before loading the data: Column Name Data Transformation Table Column Name Table Column Type Table Column Length Table Column Number of Decimal Places Description Specify transformations such as converting cases, removing blank spaces at the start or end, or formatting the values of the column as a number. For more information, see Transforming Your Data. Change the default name for the column. Change the default data type for the column, such as NUMBER, TIMESTAMP, or VARCHAR2. For more information, see About Column Types. Specify an integer value for the length of the column. You must specify a length if the column type is VARCHAR2. Don t specify a length if the type is TIMESTAMP. The maximum length is 4,000 bytes. Be careful that you don t exceed this limit when loading characters with multi-byte encoding. For columns with a numeric data type, specify an integer value for the number of decimal places to use for the data. 8. Click Next. 9. On the Review page, select Rows to be Inserted or Rows to be Updated to review the rows to be loaded. 13-4 Using Oracle Business Intelligence Cloud Service

Loading Your Files into an Existing Table 10. Click Next to load the data to the table. When the data is loaded, you see details of records that were either loaded successfully or unsuccessfully. The Summary page provides a link for you to download successfully processed records. If you encountered errors, a second link is provided to download the unsuccessfully processed records. 11. Optionally, click Download Records to open or save a Microsoft Excel file of the records that were processed successfully or unsuccessfully. See Correcting Errors in Data Loads for more information. 12. Click OK. After the data is loaded, you can model it as described in Modeling Data in Oracle Business Intelligence Cloud Service. Loading Your Files into an Existing Table You can load your files into an existing table on Oracle Database Cloud Service (Database Schema). For example, you might want to upload two new columns that were added to a table, or you might want to overwrite columns whose names have changed. Video To load data into an existing table using Data Loader: 1. Sign in to Oracle BI Cloud Service. 2. On the Home page, click Load Data. Loading Data from Files 13-5

Loading Your Files into an Existing Table 3. In Data Loader, click the Load Data button. 4. Use the Select Data page to specify the data to load into the database. Click Upload to select a file from which to upload data, and then click Open. Alternatively, you can copy the data from another source and paste it into the preview pane on the page. The data loads into the pane and becomes read-only. If the results aren t what you expected to see in the preview pane, then click Clear to remove pasted or uploaded text, and then try again. 5. Optionally, specify the following on the Select Data page: Field or Element Ignore the first number lines The first line contains header names Delimiter Description Enter the number of first rows to skip during loading. For example, you might want to skip rows that are related to the title of the file. Select this option to indicate that the first row of data to load contains header names. The first row of data is the one after the number of rows that you specified to skip. Select the type of delimiter that is used to separate the data that your file. The delimiter can be a Comma, Pipe, or Tab. 6. Click Next. 7. On the Select Destination page, select Existing Table, and then select the table name. Select whether to remove existing data before loading the updated data. Data Loader provides a proposed mapping of the first row, the destination table, and the uploaded data. Review the proposed mapping, and then optionally apply the following changes before loading the data: Column Name Data Column Name Data Transformation Update Row on Match Description Select which column to load for each row. Compare the Data Column Name with the Table Column Name to ensure that the columns will load appropriately. Select Do not load this column to skip loading for that row. Specify transformations, such as converting cases, removing blank spaces at the start or end, or formatting the values of the column as a number. See Transforming Your Data for more information. Select this option to update (overwrite) data when the uploaded data matches the data for the destination column. If the data doesn t match, or if you don t select this option, the data is inserted (appended). Note that in some cases, you need to select multiple columns to identify matching columns (for example, customer first name and customer last name). 13-6 Using Oracle Business Intelligence Cloud Service

Viewing Data Load History 8. Click Next. 9. On the Review page, select Rows to be Inserted or Rows to be Updated to review the rows to be loaded. 10. Click Next to load the data to the table. When the data is loaded, you see details of records that were loaded successfully or unsuccessfully. The Summary page provides a link for you to download successfully processed records. If you encountered errors, a second link is provided to download the unsuccessfully processed records. 11. Optionally, click Download Records to open or save a comma-separated file of the records that were processed successfully or unsuccessfully. You can open this file in Microsoft Excel. See Correcting Errors in Data Loads for additional information. 12. Click OK. Viewing Data Load History After loading data into new or existing tables, you can view reports of previous data loads. For example, you can view a report about data that you loaded yesterday from Microsoft Excel. To view the results of previous data loads: 1. Sign in to Oracle BI Cloud Service and click Load Data. Loading Data from Files 13-7

Viewing Data Load History The Home page in Data Loader shows information about previous data load operations. 2. Click a link in the list of reports to display details for that data load operation. For example, click the number of inserted records to see a report of the rows that were added. See Correcting Errors in Data Loads for additional information. 3. In the Search bar, use the Search button to filter the reports. Select All Columns or select a column name to search only results displaying in a specific column, and then enter a search string and click Go. For example, you can create filters, such as "User contains default" or "Inserted Records contains 100." 4. Optionally, create filters by clicking on the headers for each column in the report to display a list in which you select a particular value for the filter. Select Sort Ascending or Sort Descending to sort your column. 13-8 Using Oracle Business Intelligence Cloud Service

Correcting Errors in Data Loads You can add (or remove) a Control Break in a column header. A Control Break separates the report into various categories, depending on the data. The figure shows that the Control Break occurs on the Inserted Records column and separates content into different headers taken from the distinct operation on the values of that column. Correcting Errors in Data Loads If you find that some data records do not load, then you can display a report of the errors that occurred and correct those errors. Video When you load data, you might: See numeric data type mismatches A common error when loading data results from a mismatch of data types between the loaded data and the database table structure. Look for yellow shading that indicates these types of errors. To resolve this error, select the Format as a number data transformation for all numeric columns during a data load. See Transforming Your Data for additional information. Load data to a table or experience a system issue that prevents all of your data from properly loading. You can resolve this issue by removing all data in the existing table and starting over. You can reload the data and set the Remove existing data before loading new data option on the Select Data page. Load data to the incorrect column or make a similar mistake that requires you to modify tables in Oracle Database Cloud Service (Database Schema). You can use Oracle APEX utilities for more extensive maintenance, such as dropping tables and uploading, inserting, and deleting data from existing tables. See About PL/SQL Database Scripts for additional information on Oracle APEX. To review data load issues, you click the errors on the page that are highlighted in red (by default). Because the details report is filtered, click Reload Records. The Select Destination page and certain options are selected by default. You can load the number of records that match the filter. This number is the same as the last number that is displayed on the report pagination element at the bottom of the page. To resolve errors in attempts to load data: 1. Sign in to Oracle BI Cloud Service, and then click Load Data. The Home page in Data Loader shows information about previous data load operations. 2. In the Not Loaded Records column, click a number greater than zero. Loading Data from Files 13-9

Correcting Errors in Data Loads 3. You use the Load Details page to view information about the records that were processed and those that encountered errors. For example, you might see that the value of a record was too large for the column. 4. Optionally, click Download ERROR Records to save the error report to a CSV file. When you have downloaded the error records, you can correct and re-load them as appropriate. 5. Optionally, click Reload Records to display the Select Destination page, from which you can specify a new or existing table for the uploaded data. Select Remove existing data before loading new data on the Select Data page to remove data before loading. 13-10 Using Oracle Business Intelligence Cloud Service

14 Loading Data from Relational Tables This topic describes how to load relational tables. Topics: Loading Relational Tables Using SQL Developer Loading On-Premises Relational Sources and Files to the Cloud Using Oracle BI Cloud Service Data Sync Loading Relational Tables Using SQL Developer You can use Oracle SQL Developer Release 3.2 or later along with your Oracle Database Cloud Service (Database Schema) Secure File Transfer Protocol (SFTP) server to upload and administer data in Oracle Database Cloud Service (Database Schema). Oracle SQL Developer is an integrated, transparent, and seamless bulk-data loading facility with full object browsing capabilities. This Java-based tool runs on a client machine and accesses your Oracle Database Cloud Service through a set of RESTful Web Service calls that allow you to access and load data and data structures into Oracle Database Cloud Service. See REST API for Oracle Java Cloud Service for additional information. You can: Connect to the database through Oracle SQL Developer. Note: To configure Oracle SQL Developer connections for uploading data, refer to the Add any Oracle SQL Developer object. Data Loading and the Oracle Database Cloud Service tutorial. Move data from on-premises databases to any target Cloud database. Create deployment shopping carts. Oracle SQL Developer creates a cart containing objects that you want to load into your service, connects to your service, and then securely deploys data from the cart to the service. You can also compare the environments and carts. Load data incrementally on a schedule by using Oracle SQL Developer. See Using SQL Developer for Data Loading in Using Oracle Database Cloud Service (Database Schema) for more information. Note: Oracle SQL Developer uses the database utility SQL*Loader to perform the data load. To find out more about restrictions on data loading, see the Oracle Database Utilities book. Loading Data from Relational Tables 14-1

Loading On-Premises Relational Sources and Files to the Cloud Using Oracle BI Cloud Service Data Sync As a guideline, use Oracle SQL Developer to input files greater than 500,000 rows. See Using SQL Developer for Data Loading in Using Oracle Database Cloud Service (Database Schema) for more information. Note: Prior to loading data into an existing schema or table, consider backing up your data for safekeeping. See Using Oracle Database Backup Service for additional information. Loading On-Premises Relational Sources and Files to the Cloud Using Oracle BI Cloud Service Data Sync Oracle BI Cloud Service Data Sync is a wizard-driven utility that enables you to upload on-premises relational sources or CSV files to Oracle Database Cloud Service. Consider using Oracle BI Cloud Service Data Sync when you want to: Load data sources other than Oracle. Load a combination of data sources, such as CSV and Oracle relational files. Perform incremental data loads or rolling deletes. Perform insert-only or append strategies. Merge data from multiple sources. Schedule data loads. You can replace, append, and update data in tables by scheduling data loads and using the Load Strategy option of this utility. Use Oracle BI Cloud Service Data Sync to load relational files from these databases: Oracle DB2 Microsoft SQL Server 14-2 Using Oracle Business Intelligence Cloud Service

Loading On-Premises Relational Sources and Files to the Cloud Using Oracle BI Cloud Service Data Sync MySQL Teradata TimesTen You can: Interactively load data. Schedule data loads for one or more tables. Run and monitor data loads. For both initial and incremental data loads in Oracle Database Cloud Service, you can append, replace, and update data in tables. You can download Oracle BI Cloud Service Data Sync tool from Oracle Technology Network (OTN) software downloads page. This tool synchronizes on-premises data with Oracle BI Cloud Service by using the Oracle BI Cloud Service REST API. Note: Oracle BI Cloud Service Data Sync is not officially released. Oracle does not support this tool and does not guarantee that it will be supported in future releases. The design and implementation of this tool may change, and upgrade of this tool is not guaranteed. Loading Data from Relational Tables 14-3

15 Automating Loading Data Using Programmatic Methods This topic describes how to use programmatic methods to load your data. Generally, you use these methods to load large volumes of data, perform complex transformations, create indexes, and perform database management and monitoring tasks. Topics: About the Oracle BI Cloud Service REST API About the Oracle Database Cloud Service API About PL/SQL Database Scripts About the Oracle BI Cloud Service REST API You use the Oracle BI Cloud Service REST API to define or customize your own API and programmatically load on-premises data on Oracle Database Cloud Service. Once data is loaded on to a cloud database, you can manage the data, load schemas and tables, and so on. The Oracle BI Cloud Service REST API is optimized for loading large volumes of data (thousands to millions) from one or more sources. You can: Insert, update, upsert, and delete large numbers of records by streaming batches of records. Update statistics. Drop or create indices on tables on the Oracle Database Cloud Service. Write programs and scripts in your favorite programming language and then combine them with additional application logic to invoke the Oracle BI Cloud Service REST API. Invoke the script or application with your on-premises scheduler. Automate incremental data loading or integrate with ETL tools using the Oracle BI Cloud Service REST API. See Oracle Cloud REST API Reference for Oracle Business Intelligence Cloud Service for additional information. Create a customized API using the Oracle BI Cloud Service REST API framework. About the Oracle Database Cloud Service REST API Oracle Database Cloud Service (Database Schema) only. You can create RESTful Web Services to access SQL and PL/SQL queries in Oracle Database Cloud Service Automating Loading Data Using Programmatic Methods 15-1

About PL/SQL Database Scripts (Database Schema) from outside the cloud. You use the RESTful Web Services wizard to create RESTful Web Services. The RESTful wizard provides a mechanism to access the service and enables you to define a set of Uniform Resource Identifiers (URIs) to a SQL query or PL/SQL script. You can call out to any SQL query to read any data and return a result, or call out to PL/SQL code to read, write, modify, or delete data. You can define your own REST API that can be invoked from on-premises environments. You can define any PL/SQL block with BIND variables that can modify tables in Oracle Database Cloud Service (Database Schema). In addition, you can use the APEX_WEB_SERVICE API within a PL/SQL block to invoke any REST or SOAP API that is supported by cloud applications and retrieve data from an external system. The data can be transferred directly from the onpremises source to the cloud database. You can then programmatically automate the web service. See Implementing RESTful Web Services in Using Oracle Database Cloud Service (Database Schema). About PL/SQL Database Scripts Oracle Database Cloud Service (Database Schema) only. You can use PL/SQL database scripts to load data from external, generic web services. You can retrieve and load data from other cloud services, such as Oracle s Fusion Cloud or Salesforce.com. The API can be called from your PL/SQL code created by using SQL Workshop, a robust developer s tool that you use to create user-friendly, front-end applications to execute complex database operations (for example, data entry applications that execute PL/SQL to pass parameters entered by users). 15-2 Using Oracle Business Intelligence Cloud Service

About PL/SQL Database Scripts SQL Workshop is part of Oracle Application Express (APEX). Oracle APEX is Oracle's primary tool for developing web applications with SQL and PL/SQL. Using only a web browser, you can develop and deploy professional Web-based applications for desktops and mobile devices. You can build PL/SQL scripts in SQL Workspace that: Author and execute SQL queries against objects in the Database Schema Service. Author and execute database procedures. Maintain database objects. For example, you can: Create and maintain indices to improve performance. Drop unneeded objects, such as tables. Create views to expose functionality in the database. Add columns. Modify objects created post-load, such as conform date types. Perform post-load transformations. See SQL Syntax in Using Oracle Database Cloud Service (Database Schema). Automating Loading Data Using Programmatic Methods 15-3

Part V Modeling Data in Oracle Business Intelligence Cloud Service This part explains how to model data in Oracle Business Intelligence Cloud Service. Chapters: Understanding Data Modeling Starting to Build Your Data Model Defining Hierarchies and Levels for Drilling and Aggregation Securing Your Data Model

16 Understanding Data Modeling You can build a model of your business data using Oracle Business Intelligence Cloud Service. Topics: About Modeling Data Planning a Data Model Roadmap for Modeling Data About Modeling Data A data model is a design that presents business data for analysis in a manner that reflects the structure of the business. Data models enable analysts to structure queries in the same intuitive fashion as they ask business questions. Well-designed models are simple and mask the complexity of the underlying data structure. Tip: Before modeling data, ensure that you understand the data modeling definitions that are included in Oracle BI Cloud Service Terminology. Data Modeler enables you to model data in Oracle BI Cloud Service. Using Data Modeler you can model data from various source types, such as star and snowflake, in various ways that make sense to business users. You must have the BIDataModelAuthor role to use Data Modeler. Although not all source objects have star relationships, Data Modeler presents data as a simple star structure in the data model. In other words, the data model represents measurable facts that are viewed in terms of various dimensional attributes. When building the data model, you perform the following tasks: Add source tables or views to the model and classify them as either a fact table or a dimension table. Define joins between fact and dimension tables Ensure that every dimension table maps to at least one fact table, and that every fact table maps to at least one dimension table. Specify aggregation rules for different fact columns, create derived measures based on expressions, create dimension hierarchies to support drilling, and create levelbased measures. Publish your data model to permanently save the changes and make the data available for use in analyses. Understanding Data Modeling 16-1

Planning a Data Model Source data from files or relational sources must be uploaded to destination tables in the Oracle Database Cloud Service integrated with Oracle BI Cloud Service. See How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service? and Loading Data in Oracle Business Intelligence Cloud Service. After you create your data model, you can start creating analyses from the Home page of Oracle BI Cloud Service. Your data model displays as a subject area that you can use for creating analyses. The name of the subject area matches the name of your data model. Note that when you model source objects with multiple star relationships, they are all part of the same data model and are included in the same subject area. Planning a Data Model Before using Data Modeler in Oracle BI Cloud Service, take some time to think about your business requirements and to understand data modeling concepts. Topics: Understanding Data Model Requirements Components of Data Models About Modeling Source Objects with Star Relationships About Modeling Source Objects with Snowflake Relationships About Modeling Denormalized Sources About Modeling Normalized Sources Understanding Data Model Requirements Components of Data Models Before you can begin to model data, you must first understand your data model requirements: What kinds of business questions are you trying to answer? What are the measures required to understand business performance? What are all the dimensions under which the business operates? Or, in other words, what are the dimensions used to break down the measurements and provide headers for the reports? Are there hierarchical elements in each dimension, and what types of relationships define each hierarchy? After you have answered these questions, you can identify and define the elements of your business model. Fact tables, dimension tables, joins, and hierarchies are key components you will come across when building your data model in Oracle BI Cloud Service. Component Fact Tables Description Fact tables contain measures (columns) that have aggregations built into their definitions. 16-2 Using Oracle Business Intelligence Cloud Service

Planning a Data Model Component Dimension Tables Joins Hierarchies Description Measures aggregated from facts must be defined in a fact table. Measures are typically calculated data such as dollar value or quantity sold, and they can be specified in terms of hierarchies. For example, you might want to determine the sum of dollars for a given product in a given market over a given time period. Each measure has its own aggregation rule such as SUM, AVG, MIN, or MAX. A business might want to compare values of a measure and need a calculation to express the comparison. A business uses facts to measure performance by well-established dimensions, for example, by time, product, and market. Every dimension has a set of descriptive attributes. Dimension tables contain attributes that describe business entities (like Customer Name, Region, Address, or Country). Dimension table attributes provide context to numeric data, such as being able to categorize Service Requests. Attributes stored in this dimension might include Service Request Owner, Area, Account, or Priority. Dimension tables in the data model are conformed. In other words, even if there are three different source instances of a particular Customer table, the data model only has one table. To achieve this, all three source instances of Customer are combined into one using database views. Joins indicate relationships between fact tables and dimension tables in the data model. When you create joins, you specify the fact table, dimension table, fact column, and dimension column you want to join. Joins allow queries to return rows where there is at least one match in both tables. Tip: To return rows from one table where there no matching rows in other table, use the option Include Null Values. See Suppressing Null Values in Views. Hierarchies are sets of top-down relationships between dimension table attributes. In hierarchies, levels roll up from lower levels to higher levels. For example, months can roll up into a year. These rollups occur over the hierarchy elements and span natural business relationships. About Modeling Source Objects with Star Relationships Star sources consist of one or more fact tables that reference any number of dimension tables. Because Data Modeler presents data in a star structure, working with star sources is the simplest modeling scenario. In star sources, dimensions are normalized with each dimension represented by a single table. For example, assume that you have separate sources for Revenue Measures, Products, Customers, and Orders. In this scenario, you load data from each source to separate database tables. Then, you use Data Modeler to create a fact table (Revenue Measures) and dimension tables (Products, Customers, and Orders). Finally, you create joins between the dimension tables and the fact table. When you create your fact and dimension tables, you can drag and drop the source objects into the data model, or you can use menu options to create the fact and dimension tables individually. See Roadmap for Modeling Data for a full list of data modeling tasks. Understanding Data Modeling 16-3

Planning a Data Model About Modeling Source Objects with Snowflake Relationships Snowflake sources are similar to star sources. In a snowflake structure, however, dimensions are normalized into multiple related tables rather than in single dimension tables. For example, assume that you have separate sources for Revenue Measures, Products, Customers, and Orders. In addition, you have separate sources for Brands (joined to Products) and Customer Group (joined to Customers). The Brands and Customer Group tables are considered to be "snowflaked" off the core dimension tables Customers and Products. In this scenario, you load data from each source to separate database tables. Next, you create database views that combine the multiple dimension tables into a single table. In this example, you create one view that combines Products and Brand, and another view that combines Customer and Customer Group. Then, you use Data Modeler to create a fact table (Revenue Measures) and dimension tables (Products + Brand view, Customers + Customer Group view, and Orders). Finally, you create joins between the dimension tables and the fact table. See Roadmap for Modeling Data for a full list of data modeling tasks. About Modeling Denormalized Sources Denormalized sources combine facts and dimensions as columns in one table (or flat file). With a denormalized flat source, one data file is loaded into one table. The data file consists of dimension attributes and measure columns. In some cases, the data model might consist of a hybrid model that involves a combination of star, snowflake, and denormalized sources. For example, a denormalized source might include information about revenue measures, products, customers, and orders - but all in a single file rather than in separate source files. In this scenario, you first load the denormalized file as a single database table. Then, you use the Add to Model wizard to partition columns into multiple fact and dimension tables. In this example, you drag and drop revenue measure columns to create a fact table, then drag and drop columns for products, customers, and orders to create three separate dimension tables. Finally, you create joins between the dimension tables and the fact table. See Roadmap for Modeling Data for a full list of data modeling tasks. About Modeling Normalized Sources Normalized or transactional sources distribute data into multiple tables to minimize data storage redundancy and optimize data updates. In a normalized source, you have multiple data files that correspond to each of the transactional tables. Data from Oracle Cloud applications is likely partitioned into a normalized source. Similar to snowflake sources, modeling normalized sources involves creating database views to combine columns from multiple source tables into individual fact and dimension tables. Some normalized sources are very complex, requiring a number of database views to organize the data into a star-type model. For example, assume that you have source files for Products, Customers, Orders, and Order Items. Orders and Order Items both contain facts. 16-4 Using Oracle Business Intelligence Cloud Service

Roadmap for Modeling Data In this scenario, you first load the files as separate database tables. Next, you create a database view that combines the multiple fact columns into a single table. In this example, you create a view that combines columns from Orders and Order Items. Then, you use Data Modeler to create a fact table (Orders + Order Items view) and dimension tables (Products and Customers). Finally, you create joins between the dimension tables and the fact table. See Roadmap for Modeling Data for a full list of data modeling tasks. Roadmap for Modeling Data This roadmap shows you all the tasks related to creating and working with data models in Oracle BI Cloud Service: Task Description More Information Read about Data Modeler Browse source objects Create database views as needed Create fact tables and dimension tables Join fact and dimension tables Create a time dimension Create aggregated and calculated measures Create hierarchies and levels Create variables Set up object permissions Set up data security filters Become familiar with Data Modeler, including how to refresh data, publish changes, and use Action menus. Review source tables to determine how to structure your data model Create views for role-playing dimensions, or create views to combine multiple tables into one, as in snowflake or normalized sources. Use source objects to create dimension tables and fact tables in your data model. Join dimension tables to your fact table Use the Create Time Dimension wizard to create a time source table with time data, a corresponding time dimension table, and a time hierarchy Specify aggregation for columns and create calculated measures using custom expressions Define hierarchies and levels based on relationships between groups of attribute columns Optionally, create variables that dynamically calculate and store values for use in column expressions and data filters Define object permissions that control access to fact tables, dimension tables, and columns Define row-level data security filters for fact tables, dimension tables, and columns Using Data Modeler Reviewing Source Tables and Data Adding Your Own Source Views Adding Fact Tables and Dimension Tables to the Data Model Joining Fact and Dimension Tables Creating a Time Dimension Using Columns in the Data Model Editing Hierarchies and Levels Defining Variables Securing Access to Objects in the Model Defining Data Security Filters Understanding Data Modeling 16-5

17 Starting to Build Your Data Model This section provides information about first steps for building a data model, such as adding dimension tables, fact tables, and joins. Topics: Typical Workflow for Starting a Data Model Using Data Modeler Reviewing Source Tables and Data Adding Your Own Source Views Adding Fact Tables and Dimension Tables to the Data Model Joining Fact and Dimension Tables Creating a Time Dimension Using Columns in the Data Model Copying Model Objects Typical Workflow for Starting a Data Model Here are the common tasks to start modeling data. Task Description More Information Read about Data Modeler Browse source objects Create database views as needed Create fact tables and dimension tables Joining fact and dimension tables Add a time dimension table and source table Get familiar with the areas and features of the tool Review source tables to determine how to structure your data model Create views when you need to combine multiple source tables into a single dimension table Create a data model by defining fact tables and dimension tables Create joins between tables Create a time dimension table and database source table with time data Using Data Modeler Reviewing Source Tables and Data Adding Your Own Source Views Adding Fact and Dimension Tables to the Data Model Joining Fact and Dimension Tables Creating a Time Dimension Starting to Build Your Data Model 17-1

Using Data Modeler Task Description More Information Create aggregated and calculated measures Create derived attributes Specify aggregation for measure columns and create custom measures using expressions Specify custom attributes for dimension tables using expressions Using Columns in the Data Model Creating Derived Attributes Using Data Modeler Data Modeler enables you to model the data that is needed to produce analyses. Topics: Opening Data Modeler Opening Data Modeler Using the Left Pane in Data Modeler Using the Right Pane in Data Modeler Using Action Menus Locking the Data Model Validating the Data Model Refreshing and Synchronizing Source Objects and Data Model Objects Publishing Changes to the Data Model Clearing Cached Data Deleting the Data Model Renaming the Data Model Open Data Modeler from the Oracle Business Intelligence Cloud Service Home page. 1. Sign in to Oracle Business Intelligence Cloud Service. 2. Click Model on the Home page. Using the Left Pane in Data Modeler Various data modeling menus are available from the left pane in Data Modeler. To filter the display of objects in the left pane: 1. In Data Modeler, in the left pane, open the Database, Data Model, Variables, or Roles menu. 2. Click the Filter icon to the right of the selected menu. 17-2 Using Oracle Business Intelligence Cloud Service

Using Data Modeler 3. In the Filter area, enter a string value for filtering the display. 4. Delete the text or click the Filter icon again to remove the filter. Using the Right Pane in Data Modeler The right pane in Data Modeler is a contextual pane that changes depending on what task you are performing. After you have started modeling data, the default or home view shows the fact tables, dimension tables, and joins that you have defined so far. In the fact tables and dimension tables area you can see the number of joins for each fact and dimension table, as well as the number of measures in each fact table. Starting to Build Your Data Model 17-3

Using Data Modeler Joins are listed below the fact and dimension tables. Click the up or down arrow in each column header to sort. Using Action Menus When you click an object to open its editor, the editor appears in the right pane. For example, clicking a dimension table name from the Data Model menu in the left pane opens the dimension table editor in the right pane. Data Modeler provides Action menus for most objects. Action menus are represented by a gear icon. Action menus contain actions that are relevant for a particular object or context, and are visible when the object is selected. For example, select a source object in the Database menu in the left pane to see its Action menu. A global Model Actions menu is also provided in the upper right corner. You use the global Model Actions menu for tasks that apply to the entire data model, such as renaming, deleting, refreshing, or unlocking the model. Deleting Individual Data Model Objects in Data Modeler You can use Action menus to delete data model objects. Note the following about deleting objects: You must lock the model before deleting an object. You can delete source views, but you cannot delete source tables. Use SQL Workshop to drop source tables in Oracle Database Cloud Service (Database Schema). You cannot delete model objects upon which other objects depend. For example, you cannot delete a dimension table that is joined to another table until the join is removed. Similarly, you cannot delete a column that is being used in an expression, or a source view that is being used in another view. Objects are not truly deleted until changes are published, with the exception of source views. Source views are deleted when you complete the action. 17-4 Using Oracle Business Intelligence Cloud Service

Using Data Modeler Locking the Data Model You must always lock the data model before making any changes. Click Lock to Edit to lock the data model. Always publish changes you want to keep before leaving Data Modeler for an extended length of time. When your HTTP browser session times out (after 20 minutes of inactivity), the lock is released and any unpublished changes are discarded. Similarly, closing a browser ends the HTTP session and discards any unpublished changes. However, closing the browser does not release the lock. In this case, you can start a new session in a new browser and sign in with the same user name. When you attempt to lock the model in the new session, Data Modeler asks whether you want to reacquire the lock. Changing Database Views You must also lock the model if you want to change database views from Data Modeler. Changes you make to database views are immediately saved to the database. This is different to data model changes which are only saved when you publish them. Locking the model prevents other users from changing database views using Data Modeler. The lock does not stop someone from modifying database objects using other tools, such as APEX and SQL Developer. Overriding Locks If you have administrative privileges, you can override locks set by other users. To do this, select Override Lock from the global Model Actions menu in the upper right corner. Overriding a lock discards changes made by other users in their browser sessions. You must have the BIServiceAdministrator role to override a lock. Validating the Data Model You can use the global Validate checkmark icon whether the data model is valid. in the upper-left corner to check Video The data model is also validated automatically when you publish changes. Validation errors are shown at the bottom of the right pane. Use the Message Actions menu to customize the types of messages displayed (Errors, Warnings, and Information). Some tasks are validated when they are performed. For example, you cannot save a source view unless its SQL query is valid. Expressions for calculated measures and derived columns must be valid before they can be saved. Validation messages that are Starting to Build Your Data Model 17-5

Using Data Modeler displayed as you are performing tasks provide more information about any validation errors. Refreshing and Synchronizing Source Objects and Data Model Objects Data Modeler provides three ways to refresh data to ensure you are looking at the most up-to-date information. You can refresh source objects, refresh the data model, or synchronize the data model with source object definitions in the database. Refreshing Source Objects You can refresh the Database pane to ensure that the source objects list reflects the latest objects in the database. For example, you can refresh the source objects list to include any new database tables that were added. The source objects list is not refreshed automatically after new objects are loaded in to the database. To refresh source objects, select Refresh from the Database Actions menu in the left pane. Refreshing the Data Model In some cases, other Data Modeler users might have locked the model and made changes. You can refresh the data model to ensure that Data Modeler is displaying the latest version of the model. To refresh the data model, select Refresh from the Data Model Actions menu in the left pane. Alternatively, select Refresh from the Model Actions gear menu to Edit button. next to the Lock Synchronizing with the Database You can synchronize the data model with source objects in the database. Synchronization identifies objects in the model that have been deleted in the database, as well as tables and columns that are new. It also identifies other discrepancies like column data type mismatches. To synchronize all model objects and source objects with the database, select Synchronize with Database from the global Model Actions menu in the upper right corner. To synchronize individual fact tables or dimension tables, select Synchronize with Database from the Actions menu for the given fact table or dimension table in the Data Model objects list in the left pane. Then, click OK. You must lock the data model to synchronize with the database. 17-6 Using Oracle Business Intelligence Cloud Service

Using Data Modeler Synchronization discrepancies are displayed in a message box at the bottom of the right pane. Use the Message Actions menu to customize the types of messages displayed (Errors, Warnings, and Information), select or deselect all messages, and perform sync-up actions on selected messages. For example, you can select all data type mismatch warnings and then select Sync-up selected from the Actions menu to make the relevant synchronization changes. Publishing Changes to the Data Model As you update a data model, you make changes that you can save or discard. You publish a model to save the changes permanently and make the data available for use in analyses. The published data model is displayed as a subject area in Oracle BI Cloud Service. Video Tip: Although changes to the data model are saved as you work, they are saved in the browser session only. The changes are not truly saved until you publish the model. When you publish a data model, it is validated automatically. Any validation errors appear in the bottom of the right pane. If you see validation errors, fix them and then try to publish the data model again. After making changes to your data model, you can perform these actions using the menus in the upper right corner: Publish and Unlock Verifies that the model is valid, saves the changes, and publishes the model for use with analyses. The model is unlocked for other users. Publish and Keep Lock Verifies that the model is valid, saves the changes, and publishes the model for use with analyses. The lock is retained for further edits. Starting to Build Your Data Model 17-7

Using Data Modeler Clearing Cached Data Unlock Removes the lock on the model so that other users can update it. Your unpublished changes to the model are discarded. Revert Returns the model to its previously published state. Your unpublished changes to the model are discarded, but the model remains locked. You can also click Undo and Redo in the upper right corner to revert or reapply individual changes. Tip: You do not need to publish the model to save database changes. Changes made to database views and other source database objects are saved to the database when you complete the action, not to the data model. For database changes, Undo and Redo are not available. After publishing your model it takes up to two minutes for changes to the data model to reflect in analyses and dashboards. To see changes immediately, open the analysis and click Refresh > Reload Server Metadata. Oracle BI Cloud Service caches data to maximize high performance access to data. This means data updates may not immediately reflect in analyses, dashboards, and Data Modeler. After loading new data in your tables, you might want to clear the cache to see your new data: To see new data in Data Modeler, select the Refresh Model menu. To see new data in analyses and dashboards, manually clear the cache from the Data Model menu in the left pane: To clear cached data for a particular fact or dimension table, right-click the table and select Clear Cached Data. To clear all cached data, click Data Model Actions, then select Clear All Cached Data to remove all data from the cache. You can also select Clear All Cached Data from the global Model Actions menu in the upper-right corner. Tip: Deleting the Data Model Always clear the cache manually after loading new data to ensure that the most recent data is displayed in analyses. You can delete all objects from your data model if you want to clear your model and start over. To remove all objects from your data model, select Delete Model from the global Model Actions menu in the upper right corner. This action permanently removes all data model objects. The model objects are not recoverable after you delete the model. Before deleting the model, Oracle recommends that you or your administrator take a snapshot of the model as a backup. For instructions, see Backing Up and Restoring. 17-8 Using Oracle Business Intelligence Cloud Service

Reviewing Source Tables and Data Renaming the Data Model To rename your data model, select Rename Model from the global Model Actions menu in the upper right corner. This action also renames the corresponding subject area in analyses and dashboards. Reviewing Source Tables and Data This topic describes how you can learn more about the source database objects that are available for your data model. Video Topics: Viewing Source Objects Viewing Source Objects Previewing Data in Source Objects You can see a list of source tables and views in the Database menu in the left pane. Click a table or view to see its properties. The Overview tab for source tables and views shows column information, like column name, data type, whether it s unique, and whether it accepts null values. The Data tab enables you to preview data, as described in Previewing Data in Source Objects. Previewing Data in Source Objects You can preview database tables and views to see the first 25 rows of data. By reviewing the initial rows, you can get ideas for modeling the database tables and views as either dimension tables or fact tables. To preview data in database tables and views: 1. From the Database menu in the left pane, click a database table or view to open it. 2. Click the Data tab. 3. Review the first 25 rows of data for the table or view. You can resize the columns in the display table if needed. Starting to Build Your Data Model 17-9

Creating Source Views 4. Click Get Row Count to retrieve a complete row count for the table or view. This take might take some time to complete if the table is large. 5. Click Done. Creating Source Views Create source views as a base for model objects when you think you might want to perform subsequent changes. Video Topics: About Source Views About Source Views Defining Source Views Defining Filters for Source Views Source views are saved queries of data in the database. You can think of a source view as a "virtual table." In Oracle BI Cloud Service, you create source views when using a single table as a source for more than one dimension table. For example, you can create source views that use the Employee source table as a source for the Employee and Manager dimension tables. You also create source views when creating a dimension table that is based on multiple source tables, as in a snowflake source. For example, you can create a source view that combines columns from the Customer and Customer Group source tables to create a single Customers dimension table. You can also perform pre-aggregation calculations in a source view. For example, to create an Average Revenue column that is calculated pre-aggregation, you can include the calculation in the SQL query for the view: SELECT "BICS_REVENUE_FT1"."UNITS", "BICS_REVENUE_FT1"."ORDER_KEY", "BICS_REVENUE_FT1"."REVENUE", "BICS_REVENUE_FT1"."PROD_KEY", "BICS_REVENUE_FT1"."REVENUE"/"BICS_REVENUE_FT1"."UNITS" AS AVERAGE_REVENUE 17-10 Using Oracle Business Intelligence Cloud Service

Creating Source Views FROM "BICS_REVENUE_FT1" In general, create source views as a base for model objects when you think you might want to perform subsequent changes. Creating a data model based on source views provides greater flexibility than using source tables directly. For example, using source views makes it much easier to extend model objects, create filters, and add preaggregation calculations. Adding Your Own Source Views You can add views to the source database from Data Modeler. For example, you can create a source view that combines the Brands and Products source tables to create a single source for your dimension table. Create source views as a base for model objects when you think you might want to perform subsequent changes. You can create a view from scratch and add any column you want from other tables and views in the database. Alternatively, you can create a view by copying an existing source table or another source view. To create source views: 1. In Data Modeler, lock the model for editing. 2. From the Database menu in the left pane, click Actions, then click Create View. Initially the view is empty. You can add any column you want from other tables and views in the database. Tip: To create a view from an existing source table or source view, navigate to the database object you want to copy, click Actions, and then click Duplicate. See also Copying Model Objects. 3. In the View editor, specify the name and description for the view. Optionally deselect Remove duplicate rows if you want to include duplicate rows in the view. 4. Add columns to the database view by dragging and dropping tables or views from the Database menu into the Columns area of the View editor. Alternatively, click Add Columns, select a source database table or view, select columns, and then click Add. Starting to Build Your Data Model 17-11

Creating Source Views 5. Define aliases for columns if needed. You can also optionally move rows up or down using the Action menu for a specific row. 6. From the Joins tab, you can define joins for the view. Click Create Join, then specify the left side table, right side table, columns, and the join type. You must include more than one source table in your view to create joins. 7. From the Filters tab, you can define filters for the view, as described in Defining Filters for Source Views. 8. From the SQL Query tab, review the code for the SQL query for the source view. You can edit the SQL code for the query here, but do so only if you are very familiar with SQL code. Entering invalid SQL code can produce unexpected results. If you do edit the SQL query directly, simple updates are reflected back in the Overview, Join, and Filters tabs and you can use these tabs to further edit the view later. For example, you can include: Simple SELECT clause with aliases and DISTINCT keyword FROM clause with joins WHERE clause with filter conditions which combined with AND keyword If you use the SQL Query tab to make more advanced code changes you cannot use the Overview, Joins or Filters tabs to further edit the view. For example, if you include: SQL aggregation functions, GROUP BY clause, HAVING clause 17-12 Using Oracle Business Intelligence Cloud Service

Adding Fact Tables and Dimension Tables to the Data Model ORDER BY clause OR keyword in WHERE clause 9. Optionally, click the Data tab to preview the first 25 rows of data. You can also get a complete row count. It is best to view data only after defining joins between all tables for better performance. 10. Click Save and Close. Defining Filters for Source Views A filter specifies criteria that are applied to columns to limit the results that are returned. In other words, a filter is the WHERE clause for the view statement. For example, you can define a filter where Customer Country is equal to USA. To define a filter: 1. Create a view, as described in Defining Source Views. 2. Click the Filters tab. 3. Click Create Filter. 4. In the WHERE row, first select the column for the filter. Next, select the condition, such as "is not equal to" or "is greater than". Finally, specify the value for the filter. You can specify a variable if needed. 5. Optionally, click Create Filter again to add an "and" row to the filter. Specify the column, condition, and value. Repeat as needed. 6. To remove a row, click Actions, then select Delete. 7. Click Save. Adding Fact Tables and Dimension Tables to the Data Model Use fact tables and dimension tables to represent aspects of your business that you want to understand better. Topics: About Fact Tables and Dimension Tables Creating Fact and Dimension Tables from a Single Table or View Starting to Build Your Data Model 17-13

Adding Fact Tables and Dimension Tables to the Data Model Creating Fact Tables Individually Creating Dimension Tables Individually Editing Fact Tables and Dimension Tables Adding More Columns to Fact and Dimension Tables About Fact Tables and Dimension Tables Fact tables and dimension tables hold the columns that store the data for the model: Fact tables contain measures, which are columns that have aggregations built into their definitions. For example, Revenue and Units are measure columns. Dimension tables contain attributes that describe business entities. For example, Customer Name, Region, and Address are attribute columns. Fact tables and dimension tables represent the aspects of your business that you want to understand better. See Components of Data Models for more information. Before you begin modeling fact tables and dimension tables, make sure that the data that you need to model is available in the source tables list. Also ensure that you have created any source views upon which to base model objects. If you think the list of source objects in the database has changed since you opened Data Modeler, then you can click Refresh from the Database Actions menu. If the data that you need has not yet been loaded into the database, then you can load it as described in Loading Data in Oracle Business Intelligence Cloud Service. Creating Fact and Dimension Tables from a Single Table or View Some source tables contain both fact and dimensional data, such as in a denormalized source. For these source tables, Data Modeler provides a wizard that enables you to partition the fact and dimensional columns into fact tables and dimension tables. Video Use the wizard whenever you want to assign individual columns from a single source table or view to different fact or dimension tables. For example, assume that you have uploaded a file with both product and customer attributes, as well as revenue measures. Use the wizard to create the appropriate source views and the corresponding fact and dimension tables. To create fact and dimension tables simultaneously: 1. In Data Modeler, lock the model for editing. 2. In the Database menu in the left pane, right-click the source table that contains the fact and dimensional data that you want to model and select Add to Model, then As Fact and Dimension Tables. 17-14 Using Oracle Business Intelligence Cloud Service

Adding Fact Tables and Dimension Tables to the Data Model 3. In the Source Table area, select the one or more columns to include in the fact table. Drag and drop the columns into the Fact Table box. Tip: You can also click the Plus icon in the column header area to select a column to include in the fact table. 4. In the field above the list of columns, enter a name for the fact table, such as Costs or Measures. 5. In the Source Table area of the Add to Model wizard, select the one or more columns to include in the first dimension table to create. Drag and drop the columns into the Dimension Tables box. Click Filter near the source table name to find the columns that you need. 6. In the field above the list of columns, enter a name for the dimension table. 7. To add more dimension tables, click Add and repeat the previous two steps. 8. To delete a dimension table, click Delete next to the table name. 9. Specify the join columns for each of the dimension tables. Select the box beside the appropriate columns to mark those columns as join columns. If the join column you select is missing from the fact table it is added to the fact table for you. Starting to Build Your Data Model 17-15

Adding Fact Tables and Dimension Tables to the Data Model 10. Click Next. 11. On the next page, review the objects that will be created. 12. To add views to the database and to create the appropriate facts, dimensions, and joins, click Create. 13. When the Status columns shows that all tasks completed, click Close. Creating Fact Tables Individually In the Database pane, notice that the appropriate views have been added to the source object list. You can add individual source tables containing fact data to your data model. Video If you have distinct source tables with fact data, such as in a star source, then you can add them to your data model individually. For example, if you have a source table that contains only revenue measures, then you can use this method to create the corresponding fact table. Alternatively, you might have sources with fact information spread across multiple tables, such as normalized transactional sources. In this case, create source views first to combine tables in a way that resembles a star model. For information about creating views, see Defining Source Views. For information about modeling different source types, see Planning a Data Model. 17-16 Using Oracle Business Intelligence Cloud Service

Adding Fact Tables and Dimension Tables to the Data Model Tip: Create source views as a base for model objects when you think you might want to perform subsequent changes like extending model objects, creating filters, and adding pre-aggregation calculations. Creating a fact table based on source views provides greater flexibility than using source tables directly. When you use this method to create individual fact tables, all columns in the source table or view are assigned to a single fact table and if the source has relationships with other tables or views, we'll offer to add them to your model. After locking the model, perform one of the following actions to create fact tables individually: Drag the source table or view from the Database menu in the left pane to the Fact Tables area of the Data Model. From the Database menu in the left pane, right-click the table or view, then click Add to Model, then as Fact Table. From the Database menu in the left pane, click Table Actions or View Actions, then click Add to Model, then as Fact Table. From the Database Table or View editor for a particular source table or view, click Add to Model, then as Fact Table. In the right pane, click Add in the Fact Tables area of the Data Model. Then, select one or more source tables and views from the Database Objects list and click OK. To copy an existing fact table, click Fact Table Actions for the fact table you want to copy, and then click Duplicate. See also Copying Model Objects. After adding the source table or view to the model, you can edit the fact table, as described in Editing Fact Tables and Dimension Tables. Creating Dimension Tables Individually You can add individual source tables containing dimension data to your data model. Video If you have distinct dimensional source tables, such as in a star source, then you can add them to your data model individually. For example, if you have a source table that contains only customer attributes, then you can use this method to create the corresponding dimension table. Alternatively, for snowflake or normalized (transactional) sources, create source views to combine source objects in a way that resembles a star model. For information about Starting to Build Your Data Model 17-17

Adding Fact Tables and Dimension Tables to the Data Model creating views, see Defining Source Views. For information about modeling different source types, see Planning a Data Model. Tip: Create source views as a base for model objects when you think you might want to perform subsequent changes like extending model objects, creating filters, and adding pre-aggregation calculations. Creating a dimension table based on source views provides greater flexibility than using source tables directly. When you use this method to create individual dimension tables, all columns in the source table or view are assigned to a single dimension table and if the source has relationships with other tables or views, we'll offer to add them to your model. After locking the model, perform one of the following actions to create dimension tables individually: Drag the table or view from the Database menu in the left pane to the Dimension Tables area of the Data Model. From the Database menu in the left pane, right-click the table or view, then click Add to Model, then as Dimension Table. From the Database menu in the left pane, click Table Actions or View Actions for a table or view, then click Add to Model, then as Dimension Table. Click Add in the Dimension Tables area of the Data Model, then select Add Database Tables. From the Database Objects list, select one or more source tables and views from the list and click OK. From the Database Table or View editor for a particular source table or view, click Add to Model, then as Dimension Table. To copy an existing dimension table, click Dimension Table Actions for the dimension table you want to copy, and then click Duplicate. See also Copying Model Objects. After adding the source table or view to the model, you can edit the dimension table, as described in Editing Fact Tables and Dimension Tables. Editing Fact Tables and Dimension Tables You can edit properties of fact and dimension tables in your data model and preview the source data. To edit a fact table or dimension table: 17-18 Using Oracle Business Intelligence Cloud Service

Adding Fact Tables and Dimension Tables to the Data Model 1. In Data Modeler, lock the model for editing. 2. Click the fact table or dimension table that you want to edit. 3. Change settings on the Overview tab as needed: Field or Element Time dimension Enable skipped levels and Enable unbalanced hierarchies Column list Aggregation Description For dimension tables only. Specifies that hierarchies for this dimension table support a time dimension. For dimension tables only. Set properties for hierarchies associated with this dimension table. See Setting Dimension Table Properties for Hierarchies for information. Click the link for a column to edit that column in the Column editor. Or, right-click the row for the column and click Edit. See Editing Columns for more information. For fact tables only. Click to select a type of aggregation for the column from a dropdown list, or select Set Aggregation from the Column Actions menu. Aggregation types include: None: Applies no aggregation. Sum: Calculates the sum by adding up all values. Average: Calculates the mean value. Median: Calculates the middle value. Count: Calculates the number of rows that are not null. Count Distinct: Calculates the number of rows that are not null. Each distinct occurrence of a row is counted only once. Maximum: Calculates the highest numeric value. Minimum: Calculates the lowest numeric value. First: Selects the first occurrence of the item. Last: Selects the last occurrence of the item. Standard Deviation: Calculates the standard deviation to show the level of variation from the average. Standard Deviation (all values): Calculates the standard deviation using the formula for population variance and standard deviation. Tip: Some calculated measures show Pre-Aggregated for aggregation. These measures have calculations involving measures that already have an aggregation applied. To edit a calculation that contains pre-aggregated measures, click the column name. See also, Creating Calculated Measures. Available Edit All Add Column Click to mark a column as Available or Unavailable to choose whether that column is displayed in analyses that are created. You can also select Mark as Unavailable or Mark as Available from the Column Actions menu. You can click to edit properties for individual columns in the table, or select Edit All to edit all rows at once. Click Add Column to display the Column editor and create a new column. See Editing Columns for more information. Starting to Build Your Data Model 17-19

Adding Fact Tables and Dimension Tables to the Data Model 4. From the Source Data tab, you can preview the first 25 rows of source data for the table. Resize the columns in the display table if needed. Click Get Row Count to retrieve a complete row count for the table or view. 5. For dimension tables only: from the Hierarchies tab, edit the hierarchies and levels for the table as described in Editing Hierarchies and Levels. 6. From the Permissions tab, specify object permissions as described in Securing Access to Objects in the Model. 7. From the Data Filters tab, you can define data filters that provide row-level filtering for data model objects, as described in Defining Data Security Filters. 8. Click Done to return to the Data Model. Adding More Columns to Fact and Dimension Tables There are different ways to add more source columns to fact and dimension tables in your model. Synchronize with the database If new columns are added to a source table and you want to include them in fact tables and dimension tables in your model, synchronize the fact or dimension table with the database. Synchronization identifies any new columns and adds them to the fact or dimension table. See Refreshing and Synchronizing Source Objects and Data Model Objects. Include columns from another source (dimension tables only) Dimension tables can combine columns from multiple sources. See Adding Columns from Another Source to a Dimension Table. Adding Columns from Another Source to a Dimension Table You can add the columns from another source table or view to an existing dimension table. For example, you may want to include attributes from a Product Category table in your Products dimension table. To add columns from another source to a dimension table: 1. In Data Modeler, lock the model for editing. 2. Select the dimension table you want to edit so its Overview tab displays. 17-20 Using Oracle Business Intelligence Cloud Service

Joining Tables in the Data Model 3. Drag and drop the source table or view that contains the columns you want to add from the Database pane to the dimension table (columns area). Alternatively, right-click the dimension table you want to edit, click Add Columns, and then select the source table or view that contains the columns you want to add. 4. Select appropriate join columns and click OK. View the dimension table to see the additional columns. The Source property shows that the dimension table is based on a new database view. Data Modeler creates a new database view whenever you add columns from another source. Joining Tables in the Data Model A join in the model indicates a relationship between one fact table and one dimension table. Topics: About Joins Joining Fact and Dimension Tables About Joins A join in the model indicates a relationship between one fact table and one dimension table. When you use the Add to Model wizard in Oracle BI Cloud Service to model data, the wizard creates joins automatically between a fact table and each of its corresponding dimension tables. When you model fact and dimension tables individually, joins are automatically created between them if the join references exist in the source tables. You can also manually create joins in the data model. To do this, you drag and drop a dimension table to a fact table, or click Create Join in the Joins area. When you define a join between a fact table and dimension table, you select a join column from each table. You can create a join on more than one column. Starting to Build Your Data Model 17-21

Creating a Time Dimension Joining Fact and Dimension Tables Define joins between fact tables and dimension tables to enable querying of related data. For example, you can define a join between the Profit Metrics fact table and the Products dimension table. Video To create a join: 1. In Data Modeler, lock the model for editing. 2. In the Dimensions Tables area, drag and drop a dimension table to the Fact Tables area. Or, in the Joins area, click Create Join. 3. In the Joins area, specify the appropriate Fact Table, Fact Column, Dimension Table, and Dimension Column to use for the join. For example, you might specify a billing date column and a calendar date column. 4. Click the checkmark icon to save the changes to the join. If you want to remove your changes, then click the X icon. If you start to create a new join and click X, then the new row for the join is removed from the Joins table. After you create joins, you can see the default hierarchies and levels when you click the Hierarchies tab for the given dimension table. Creating a Time Dimension Time series functions provide the ability to compare business performance with previous time periods, enabling you to analyze data that spans multiple time periods. For example, time series functions enable comparisons between current sales and sales a year ago, a month ago, and so on. To use time series functions, the data model must include a time dimension Video When you create a time dimension, the Create Time Dimension wizard creates a table in the database, populates it with time data, creates a corresponding time dimension table in the data model, and creates a time hierarchy. The Create Time Dimension wizard populates the source table with time data from 01- JAN-1970 to 31-DEC-2020. To create a time dimension: 1. In Data Modeler, lock the model for editing. 2. In the Dimension Tables area, click Add, then Create Time Dimension. 17-22 Using Oracle Business Intelligence Cloud Service

Creating a Time Dimension You can also select Create Time Dimension from the global Model Actions menu in the upper-right corner. 3. In the Create Time Dimension wizard, specify names for the database table, the dimension table, and the hierarchy. 4. In the Hierarchy Levels, specify which levels to include, such as Year, Quarter, and Month. 5. Click Next. 6. On the next page, review the tasks that the wizard will perform to create the time dimension. 7. Click Create to enable the wizard to create the dimension. The wizard adds a time dimension with data to the database and creates a corresponding dimension in the data model. This action might take up to 30 seconds. 8. Click Done. 9. To create joins between columns in the fact table and columns in the Time dimension table, click Create Join in the data model. The time dimension has two unique columns. The DAY_TS column has the type TIMESTAMP, and the DATE_ID column has the type NUMBER. When you create a join, you specify either the column with the timestamp format or with the numeric format (depending on whether the column in the fact table has a date or number type). 10. In the Joins area for the new definition, select the appropriate fact column, then select the appropriate timestamp or numeric column from the Time dimension. Starting to Build Your Data Model 17-23

Using Columns in the Data Model After you create the joins, you can display the Hierarchies tab in the Time Dimension editor to view the default hierarchies and levels. 11. Edit the tables in the model, as described in Editing Fact Tables and Dimension Tables. 12. Click Done to return to the data model. Using Columns in the Data Model This topic describes how to use columns in the data model. Editing Columns Topics: Editing Columns Specifying Aggregation for Measures in Fact Tables Creating Calculated Measures Creating Derived Attributes Creating Expressions in the Expression Editor Use the table editor to add, edit, and delete columns in your data model. To edit a column: 1. In Data Modeler, lock the model for editing. 2. Click the fact table or dimension table that contains the column that you want to edit. If you want to edit, copy, or delete multiple columns at the same time, Shift + click or Ctrl + click the rows you want. 3. To make all columns available for editing directly in the Table editor, select Edit All. 4. In the table editor, right-click the row for a column and optionally click Copy or Delete as appropriate. 5. In the table editor, click the column that you want to edit or click Add Column. 17-24 Using Oracle Business Intelligence Cloud Service

Using Columns in the Data Model 6. Change settings on the Overview tab as needed. For fact tables, see also Creating Calculated Measures. For dimension tables, see also Creating Derived Attributes. 7. From the Permissions tab, you can modify object permissions as described in Securing Access to Objects in the Model. 8. From the Data Filters tab, you can define data filters that provide row-level filtering for data model objects, as described in Defining Data Security Filters. 9. From the Levels tab for columns in a fact table, optionally create a level-based measure as described in Setting Aggregation Levels for Measures. 10. Click Done to return to the table editor. Specifying Aggregation for Measures in Fact Tables You can specify aggregation for a measure in a fact table. For example, you can set the aggregation rule for a Revenue column to Sum. See also Setting Aggregation Levels for Measures. To specify aggregation for measures: 1. In Data Modeler, lock the model for editing. 2. In the Fact Tables area, click the fact table for which you want to create measures. 3. In the Columns list, change the aggregation rule for the appropriate columns to specify that they are measures. To apply the same aggregation rule to multiple columns, Shift + click or Ctrl + click the rows you want. Aggregation options include: None: No aggregation. Sum: Calculates the sum by adding up all values. Average: Calculates the mean value. Median: Calculates the middle value. Count: Calculates the number of rows that are not null. Count Distinct: Calculates the number of rows that are not null. Each distinct occurrence of a row is counted only once. Maximum: Calculates the highest numeric value. Minimum: Calculates the lowest numeric value. First: Selects the first occurrence of the item. Last: Selects the last occurrence of the item. Standard Deviation: Calculates the standard deviation to show the level of variation from the average. Standard Deviation (all values): Calculates the standard deviation using the formula for population variance and standard deviation. Starting to Build Your Data Model 17-25

Using Columns in the Data Model Tip: Some calculated measures show Pre-Aggregated for aggregation. These measures have calculations involving measures that already have an aggregation applied. To edit a calculation that contains pre-aggregated measures, click the column name. See also Creating Calculated Measures. 4. By default, all the columns in the fact table are displayed in analyses. Deselect the Available box for any columns that you do not want to display. You can use Shift + click or Ctrl + click to select multiple rows. 5. Click Cancel to cancel any of your changes. 6. Click Done to return to the table editor. Creating Calculated Measures If a fact table does not include all the measures that you need, then you can create calculated measures. For example, you can create a calculated measure called Average Order Size using the formula Revenue/Number of Orders. Video To create calculated measures: 1. In Data Modeler, lock the model for editing. 2. In the Fact Tables area, click the fact table for which you want to create measures. 3. In the Columns area, click Add Column. 4. In the New Column editor, enter a name and description for the column. Then, enter an expression directly in the Expression box, or click Full Editor to display the Expression editor. See also Creating Expressions in the Expression Editor for more information. 17-26 Using Oracle Business Intelligence Cloud Service

Using Columns in the Data Model 5. Expressions can contain measures that are already aggregated, as well as measures with no aggregation applied. Do one of the following: Set Aggregation to Before Calculating, if your expression includes measures that are already aggregated or aggregation is not required. Set Aggregation to After Calculating and select an aggregation rule, such as Sum, Average, Count, to apply aggregation after calculating the expression. For more information and examples, see About Creating Calculated Measures. 6. Click Done to return to the table editor. About Creating Calculated Measures Calculated measures, as the name suggests, are calculated from other measures. For example, you can create a measure that calculates Average Order Size using the formula Revenue/Number of Orders. Calculations can contain measures that are already aggregated, as well as measures with no aggregation applied. For example: Calculation includes aggregated measures: Sum(Revenue)/Sum(Orders) Calculation includes measures with no aggregation applied: UnitPrice X Quantity If the measures in your calculation are not pre-aggregated, such as UnitPrice and Quantity, you may apply aggregation after the calculation. For example, Sum(UnitPrice X Quantity). Check the measures in your calculations before choosing whether to apply aggregation Before Calculating or After Calculating your expression. See also Creating Calculated Measures. Example 1 Calculations Include Measures Already Aggregated Set Aggregation to Before calculating if the calculation contains pre-aggregated measures. For example: Sum(Revenue)/Sum(Orders) Starting to Build Your Data Model 17-27

Using Columns in the Data Model Note: If you select After calculating, any aggregation applied to measures in the calculation is ignored. Example 2 Calculations Include Non Aggregated Measures Optionally, you can apply aggregation after your calculation. Set Aggregation to After calculating and then select an aggregation rule from the drop down list. For example, Sum, Average, Count and so on. Note: When you apply aggregation after a calculation: Don t include expression columns in the calculation. If you include aggregated columns in the calculation, aggregation on the columns is ignored. 17-28 Using Oracle Business Intelligence Cloud Service

Using Columns in the Data Model Creating Derived Attributes You can create custom or derived attributes for dimension tables that are based on an expression. For example, you can use an expression to concatenate multiple address columns into a single Full Address column. Video To create derived attributes: 1. In Data Modeler, lock the model for editing. 2. In the Dimension Tables area, click the dimension table for which you want to create derived attributes. 3. In the Columns area, click Add Column. 4. In the New Column editor, enter a name and description for the column. Then, enter an expression directly in the Expression box, or click Full Editor to display the Expression editor. See Creating Expressions in the Expression Editor for more information. You can use a variable in a column expression. See Defining Variables for details. 5. Click Done to return to the table editor. Creating Expressions in the Expression Editor You can use the Expression Editor to create constraints, aggregations, and other transformations on columns. Topics: About the Expression Editor Creating an Expression About the Expression Editor When modeling data, you can use the Expression Editor to create constraints, aggregations, and other transformations on columns. For example, you can use the Expression Editor to change the data type of a column from date to character. You can also use the Expression Editor to create expressions for data filters. The Expression Editor contains the following sections: The Expression box on the left-hand side enables you to edit the current expression. The toolbar at the bottom contains commonly used expression operators, such as a plus sign, equals sign, or comma to separate items. Starting to Build Your Data Model 17-29

Using Columns in the Data Model The Expression Elements section on the right-hand side provides building blocks that you can use in your expression. Examples of elements are tables, columns, functions, and types. The Expression Elements section only includes items that are relevant for your task. For example, if you open the Expression Editor to define a calculated measure, the Expression Elements section only includes the current fact table, any dimension tables joined to that table, plus any fact tables indirectly joined through a dimension table. Similarly, when you define a derived attribute, you see the current dimension table, any fact tables joined to that table, and any dimension table joined to those fact tables. Another example is that time hierarchies are only included if the Time fact table is joined to the current table. See Expression Editor Reference for more information about items in the Expression Elements section. Creating an Expression You can use the Expression Editor to create constraints, aggregations, and other transformations on columns. To create an expression: 1. Add or edit a column from the Table editor, as described in Editing Columns. 2. Type an expression in the Expression box and click Done. Or, click Full Editor to launch the Expression Editor. 17-30 Using Oracle Business Intelligence Cloud Service

Copying Model Objects Copying Columns 3. Use the Expression Elements menus to locate the building blocks you want to use to create your expression. Drag and drop an element to add it to your expression. You can also double-click an element to insert it, or you can select the element and click the arrow icon. When you add a function, brackets indicate text that needs to be replaced. Select the text, then type, or use the Expression Elements menus to add the appropriate element. See Expression Editor Reference for information about operators, expressions, and functions. 4. Click Filter and then type text in the search box to filter the available elements. Remove the text to revert to the full list of elements. 5. Click Actions to show or hide menus under Expression Elements, or to expand or collapse all menus. 6. Click an item on the toolbar to insert an operator. 7. Click Undo or Redo as needed when building your expression. 8. Click Validate to check your work. 9. Click Save when you are finished. You can copy columns in the data model to create a new column that is an exact copy of the original column. To do this, perform one of the following actions: From the Data Model menu in the left pane, right-click the column you want to copy, and then select Copy. To copy multiple columns, Shift + click or Ctrl + click all the rows you want and then right-click to select Copy. From the Data Model menu in the left pane, click Column Actions for the column you want to copy, and then select Copy. A new column is created. The default name of the new column is the same as the original column name, with an incremental number added. Copying Model Objects Sometimes it s quicker to copy objects rather than starting from scratch. In Data Modeler you can copy fact tables, dimension tables, database tables, and database views: Starting to Build Your Data Model 17-31

Copying Model Objects Fact tables To copy an existing fact table, select Duplicate from the Fact Table Actions menu. When you copy a fact table, Data Modeler includes joins by default. See also Creating Fact Tables Individually. Aggregation level settings for measures are not copied as, in most cases, level settings in the original fact table and the copied version differ. After copying a fact table, review and set the aggregation levels for measures as required. Dimension tables To copy an existing dimension table, select Duplicate from the Dimension Table Actions menu. When you copy a dimension table, Data Modeler excludes joins default. See also Creating Dimension Tables Individually. Database tables and views. To copy an existing database object, select Duplicate from the Actions menu. When you copy a table or view, Data Modeler creates a view based on the table or view you copy. See also Defining Source Views. 17-32 Using Oracle Business Intelligence Cloud Service

18 Defining Hierarchies and Levels for Drilling and Aggregation You can define hierarchies and levels in Data Modeler. Topics: Typical Workflow for Defining Hierarchies and Levels About Hierarchies and Levels Editing Hierarchies and Levels Setting Aggregation Levels for Measures Typical Workflow for Defining Hierarchies and Levels Here are the common tasks to add hierarchies and levels to your data model. Task Description More Information Add hierarchies and levels Set aggregation levels for measures Create hierarchies and levels for your dimension tables Set custom aggregation levels for measures that are different from the default level Editing Hierarchies and Levels Setting Aggregation Levels for Measures About Hierarchies and Levels A hierarchy shows relationships among groups of columns in a dimension table. For example, quarters contain months and months contain days. Hierarchies enable drilling in reports. A dimension table can have one or more hierarchies. A hierarchy typically begins with a total level, then has child levels, working down to the lowest detail level. All hierarchies for a given dimension must have a common lowest level. For example, a time dimension might contain a fiscal hierarchy and a calendar hierarchy, with Day as the common lowest level. Day has two named parent levels called Fiscal Year and Calendar Year, which are both children of the All root level. All levels, except the total level, must have at least one column specified as the key or display column. However, it is not necessary to explicitly associate all of the columns from a table with levels. Any column that you do not associate with a level is automatically associated with the lowest level in the hierarchy that corresponds to that dimension table. Defining Hierarchies and Levels for Drilling and Aggregation 18-1

Editing Hierarchies and Levels There is no limit to the number of levels you can have in a hierarchy. The total number of levels is not by itself a determining factor in query performance. However, be aware that for extremely complex queries, even a few levels can impact performance. Editing Hierarchies and Levels After creating dimension tables, you can add hierarchies and levels to those tables. Video A hierarchy is a system of levels in a dimension that are related to each other by oneto-many relationships. For example, the Geography hierarchy might include levels for Country, State, and City. When fact tables and dimension tables are joined, a default hierarchy is created. You cannot add hierarchies for a particular dimension table until it has been joined to a fact table. Columns used in a join from a dimension table are used as key columns for the detail level in a hierarchy. To create a hierarchy and its levels: 1. In Data Modeler, lock the model for editing. 2. In the Dimension Tables area, click the dimension table for which you want to add a hierarchy. The dimension table must have at least one join to a fact table. 3. In the Dimension editor, click the Hierarchies tab. 4. In the Hierarchies area, click Add Level. The upper part of the Add Level box shows dimension columns that have not yet been used in a level. The lower part of the box shows shared levels that have already been used in another hierarchy for this table. Select the dimension column or shared level that you want to use. 5. Continue to click Add Level and select the appropriate columns or shared levels, until you have added all the levels. 6. Drag and drop levels to a different location in the order, as appropriate. You can also right-click a level and select Move left or Move right. 18-2 Using Oracle Business Intelligence Cloud Service

Editing Hierarchies and Levels 7. Click a level to display a dialog in which you can specify the level name, the key column, and the display column for the level. When you edit a shared level, the changes are made in all instances of the level. For example, if you change Country Name to Country, the level name is changed in all hierarchies where the shared level is used. 8. To delete a level, right-click the level and then click Delete, or click the level and select Delete level from the Level dialog. You cannot delete the default Total and Detail levels. When you delete a shared level, you can choose whether to delete it from the current hierarchy only, or to delete it from all hierarchies. For example, assume you want to delete the shared level Country Name from the current hierarchy only, called Hierarchy 1. Right-click the level in Hierarchy 1, select Delete, then select from Hierarchy 1. Tip: Selecting Delete level from the Level dialog only deletes the level from the current hierarchy. To remove a shared level from all hierarchies, right-click the level and select Delete, then select from all hierarchies. 9. Deselect Available if you do not want the hierarchy visible in analyses. 10. To add another hierarchy, click Add Hierarchy and repeat the steps in this procedure. Or, click Done when you are finished. Setting Dimension Table Properties for Hierarchies From the Overview tab for a particular dimension table, you can set properties that apply to all hierarchies for that table. Time dimension Specifies that hierarchies for this dimension table support a time dimension. Hierarchies for time dimensions cannot include skip levels or be unbalanced. Enable skipped levels Specifies that this dimension table supports hierarchies with skipped levels. A skip-level hierarchy is a hierarchy where there are members that do not have a value for a particular ancestor level. For example, in a Country- State-City-District hierarchy, the city "Washington, D.C." does not belong to a State. In this case, you can drill down from the Country level (USA) to the City level (Washington, D.C.) and below. In a query, skipped levels are not displayed, and do not affect computations. When sorted hierarchically, members appear under their nearest ancestors. Enable unbalanced hierarchies Specifies that this dimension table supports unbalanced hierarchies. An unbalanced (or ragged) hierarchy is a hierarchy where the leaves (members with no children) do not necessarily have the same depth. For example, a site can choose to have data for the current month at the day level, previous months data at the month level, and the previous 5 years data at the quarter level. Defining Hierarchies and Levels for Drilling and Aggregation 18-3

Setting Aggregation Levels for Measures Setting Aggregation Levels for Measures You can set aggregation levels for measures. Video For information, see About Setting Aggregation Levels for Measures. To set a custom aggregation level for a measure: 1. In Data Modeler, lock the model for editing. 2. In the Fact Tables area, click the fact table in which the measure is located. Tip: The fact table must be joined to at least one dimension table. 3. Specify the aggregation rule for the new column that you want to become the levelbased measure. 4. Click the column name, then click Levels. 5. In the Levels tab, for one or more hierarchies, use the slider to select the aggregation level for the measure. 6. Click Done to return to the table editor. About Setting Aggregation Levels for Measures By default, measures are aggregated at the level of the dimension attributes that are selected in an analysis. For example, in an analysis that includes Sales Person and Revenue columns, the Revenue is aggregated at the level of a Sales Person. To calculate ratios, you often need measures that are aggregated at a level that is different than the grain of the analysis. For example, to calculate the Revenue Percent Contribution for a Sales Person with respect to his department, you need Department Revenue at the Sales Person level in an analysis (Sales Person, Revenue, Revenue *100 / Revenue@Dept). In this example, Revenue@Dept has a custom aggregation level that is different from the default level. 18-4 Using Oracle Business Intelligence Cloud Service

19 Securing Your Data Model You can define object-level permissions and row-level security data filters for your data model in Oracle BI Cloud Service. Topics: Typical Workflow for Securing Your Data Creating Variables to Use in Expressions Securing Access to Objects in the Model Defining Data Security Filters Typical Workflow for Securing Your Data Here are the common tasks to secure your data model. Task Description More Information Define variables, if needed Create object permissions Define row-level security filters Optionally, create variables that dynamically calculate and store values for use in column expressions and data filters. Object permissions control visibility for fact tables, dimension tables, and columns. Data filters limit results returned for fact tables, dimension tables, and columns. Creating Variables to Use in Expressions Securing Access to Objects in the Model Defining Data Security Filters Creating Variables to Use in Expressions In Data Modeler, you can define variables that dynamically calculate and store values so that you can use those values in column expressions or data filters. Topics: About Variables Defining Variables Securing Your Data Model 19-1

Creating Variables to Use in Expressions About Variables Defining Variables Variables dynamically calculate and store values so that you can use those values in expressions. You can use variables in column expressions, or in data filters. For example, suppose User1 belongs to Department1 and User2 belongs to Department2. Each user must access only the data that is specific to his department. You can use the DEPARTMENT_NUMBER variable to store the appropriate values for User1 and User2. You can use this variable in a data filter in which the data is filtered by Department2 for User1 and Department2 for User2. In other words, variables dynamically modify metadata content to adjust to a changing data environment. Values in variables are not secure, because object permissions do not apply to variables. Anybody who knows or can guess the name of the variable can use it in an expression. Because of this, do not put sensitive data like passwords in variables. You cannot use a variable in an expression that defines another variable. You can create a variable for use in column expressions and data filters. For example, a variable called SalesRegion might use a SQL query to retrieve the name of the sales region of the user. Video Tip: Only reference source database objects in the SQL query for a variable. Do not include names of data model objects in the query. To define a variable: 1. In Data Modeler, lock the model for editing. 2. In the Variables menu in the left pane, click the Plus icon. 3. To create a variable that refreshes its value at the start of each user session, select Every time user signs in for Update Value. Then, enter a SQL query to populate the value of the variable. You can provide a default value if needed. Click Test to validate that the query returns an appropriate value. 19-2 Using Oracle Business Intelligence Cloud Service

Creating Variables to Use in Expressions 4. To create a variable that refreshes its value on a schedule that you set, select On a schedule for Update Value. Then, enter a SQL query to populate the value of the variable. You can provide a default value if needed. In the Run Query area, select the frequency and start date for refreshing the variable. Click Test to validate that the query returns an appropriate value. 5. To create a variable with a static value that never changes, select Do not update for Update Value and provide a value for the variable in the Value field. 6. Click Done to return to the data model. Tip: To edit an existing variable, right-click it in the Variables list and select Edit. To delete a variable, right-click it and select Delete. Securing Your Data Model 19-3

Securing Access to Objects in the Model After you have defined a variable, you can use it in a data filter or in a column expression. See Defining Data Security Filters and Creating Derived Attributes for details. Securing Access to Objects in the Model Model objects (tables and columns) are visible to all Oracle BI Cloud Service users by default. If you want to control who has access to objects in the model, then you can set show and hide permissions on individual fact tables, dimension tables, and columns. Video For example, you can restrict access to certain Revenue columns so that only authorized users can view them. To secure access to objects using permissions: 1. In Data Modeler, lock the model for editing. 2. In the Data Model, edit the fact table, dimension table, or column whose access you want to secure. 3. Select the Permissions tab. 4. To control access to the object, click Add and select the appropriate role. Alternatively, in the left pane, click Roles. Then, drag and drop a role to the Permissions list. To add multiple roles, use Shift + click or Ctrl + click to make your selections before you drag and drop. 5. Specify whether this object is visible in the analyses that are used by users with that role by selecting either Visible or Hidden. Tip: Data model objects always display to users with the BI Data Model Author role. You cannot hide objects from other data modelers. 6. To remove roles from the Permissions list, do one of the following: Right-click a role and select Remove. Select Remove from the Actions menu for that role. 19-4 Using Oracle Business Intelligence Cloud Service

Defining Data Security Filters Select multiple roles using Shift + click or Ctrl + click, then select Remove Selected from the Permissions Action menu. Remove all roles by selecting Remove All from the Permissions Action menu. Tip: 7. Click Done. About Permission Inheritance You cannot remove the Everyone role. When multiple application roles act on a user or role with conflicting security attributes, the user or role is granted the least restrictive security attribute. Also, any explicit permissions acting on a user take precedence over any permissions on the same objects granted to that user through application roles. Tip: If you deny access to a table, access to all columns in that table is implicitly denied as well. Defining Data Security Filters You can define data filters for fact tables, dimension tables, and columns that provide row-level filtering for data model objects. For example, you can create a filter that restricts access to the Products table so that only certain brands are visible to users assigned to a particular role. Video To set data filters for data model objects: 1. In Data Modeler, lock the model for editing. 2. In the Data Model, edit the fact table, dimension table, or column for which you want to set a data filter. 3. Select the Data Filters tab. 4. Add a role to the Data Filters list by doing one of the following: Click Add and select the appropriate role. In the left pane, click Roles. Then, drag and drop a role to the Data Filters list. 5. Enter an expression to specify which data is accessible for that role. Either enter the expression directly, or click Full Editor to display the Expression Editor. For information, see Creating Expressions in the Expression Editor. You can use a variable in a data filter expression. See Defining Variables for details. Securing Your Data Model 19-5

Defining Data Security Filters 6. Select Enable to specify whether the filter is enabled for that role. 7. To remove filters from the Data Filters list, do one of the following: Right-click a filter and select Remove. Select Remove from the Actions menu for that filter. Select multiple filters using Shift-click or Ctrl-click, then select Remove Selected from the Data Filters Action menu. Remove all filters by selecting Remove All from the Data Filters Action menu. 8. Click Done. 19-6 Using Oracle Business Intelligence Cloud Service

Part VI Managing Oracle Business Intelligence Cloud Service This part explains how to manage Oracle Business Intelligence Cloud Service. Chapters: Managing What Users Can See and Do Backing Up and Restoring Performing Administration Tasks

20 Managing What Users Can See and Do Administrators can manage what other users are allowed to see and do when using Oracle Business Intelligence Cloud Service. Topics: Typical Workflow for Managing What Users See and Do About Users and Roles About Application Roles Configuring What Users Can See and Do Functionality Enabled by Application Roles Typical Workflow for Managing What Users See and Do Here are the common tasks to start managing what users can see and do in. Task Description More Information Understand application roles Assign members and actions to application roles Assign application roles to users Assign application roles to user roles Add your own application roles Learn about the predefined application roles. Select which users or roles are members of an application role. Define parent application roles. Assign a single user to multiple application roles. See the roles and application roles that a user belongs to. Assign a single user role to multiple application roles. See the users who belong to a role and the application roles assigned to a role. Create your own application roles, and add members. About Application Roles Assigning Members and Actions to Application Roles Assigning Application Roles to Users Assigning Application Roles to User Roles Adding Your Own Application Roles About Users and Roles Identity domain administrators manage user accounts and assign roles for an identity domain through the My Services Security page for Oracle Cloud. The identity domain controls the authentication and authorization of users who can sign in to Oracle BI Cloud Service and other Oracle Cloud services. For more information, see Managing Users and Roles in Getting Started with Oracle Cloud. Managing What Users Can See and Do 20-1

About Application Roles Within Oracle BI Cloud Service, administrators can view users and roles that are configured for the identity domain and give them application roles specific to Oracle BI Cloud Service. It is these application roles that control what users can see and do in Oracle BI Cloud Service. See also, About Application Roles. When Oracle Cloud services are provisioned in an identity domain, several predefined roles and user accounts are available through My Services. For more information, see Roles and User Accounts Predefined in My Services in Getting Started with Oracle Cloud. Predefined Roles TenantAdminGroup <biservicename>.bicloudservic eadministrators <databaseservicename>.db_adm inistrator <databaseservicename>.db_dev eloper <databaseservicename>.db_user Description Identity Domain Administrator For users within the organization that manage users and roles for an identity domain. BI Cloud Service Administrator For users within the organization that have the role of administrator for the service. Database Administrator For users within the organization that have role of the database administrator for the service instance. Database Developer For users within the organization that have the role of database developer for the service instance. For users within the organization that have the role of database user for the service instance. About Application Roles An application role comprises a set of privileges that determine what users can see and do after signing in to Oracle BI Cloud Service. It s the administrator s job to assign people to one or more application role. There are two types of application role: Type of Application Role Predefined User-defined Description Include a fixed set of privileges. Include one or more predefined application roles. Application Roles Predefined in Oracle BI Cloud Service Oracle BI Cloud Service provides several predefined application roles to get you started. In many cases, these predefined application roles are all that you need. Tip: You can also create your own application roles. See Adding Your Own Application Roles. Predefined Application Role Description Default Members BIServiceAdministrator Allows users to administer Oracle BI Cloud Service and Identity Domain Administrator (User Role) 20-2 Using Oracle Business Intelligence Cloud Service

About Application Roles Predefined Application Role Description delegate privileges to others. Default Members BIDataModelAuthor Allows users to manage the data model in Oracle BI Cloud Service. Also allows users to upload data from files using Data Loader. BIServiceAdministra tor (Applicati on Role) BIDataLoadAuthor Allows users to load data using Oracle BI Cloud Service REST API and Oracle BI Cloud Service Data Sync. BIServiceAdministra tor (Applicati on Role) BIContentAuthor Allows users to create analyses and dashboards in Oracle BI Cloud Service. BIDataModelAuthor BIDiscoveryContent Author (Applicati on Role) BIAdvancedContentAuthor Allows users to perform more advanced content management tasks, such as add data sources for analyses and dashboards, and export dashboards. BIServiceAdministra tor (Applicati on Role) BIDiscoveryContentAuthor Allows users to visualize and explore data using Visual Analyzer, and add data sources for visualizations. BIAdvancedContent Author (Applicati on Role) BIConsumer Allows users to view and run analyses in Oracle BI Cloud Service. Use this application role to control who has access to the service. BIContentAuthor (Applicati on Role) For details about the functionality enabled by each of these predefined application roles, see Functionality Enabled by Application Roles. You cannot delete predefined application roles or remove default memberships. Each application role can have users, roles, or other application roles as members. This means that a user who is a member of one application role might indirectly be a member of other application roles. For example, a member of the BIServiceAdministrator application role inherits membership of other application roles, such as BIDataModelAuthor and BIConsumer. Any user that is a member of BIServiceAdministrator can do and see everything that these other application roles can do and see. Therefore you do not need to add a new user (for example, John) to all these application roles. You can simply add the user to the BIServiceAdministrator application role. Managing What Users Can See and Do 20-3

Configuring What Users Can See and Do Configuring What Users Can See and Do Administrators assign application roles to determine what other users can see and do in Oracle BI Cloud Service. Video Topics: Getting Started with Application Role Management Assigning Members and Actions to Application Roles Why is Membership of the BI Service Administrator Application Role Important? Assigning Application Roles to Users Assigning Application Roles to User Roles Adding Your Own Application Roles Deleting Application Roles Getting Started with Application Role Management You configure what users see and do in Oracle BI Cloud Service using the Application Role Management page. This page presents the data in 3 different views: Application Role Management Page Users tab Roles tab Application Roles tab Description This shows users from the identity domain associated with your service. Users cannot be added or changed through Oracle BI Cloud Service, but they can be added as members to application roles. The Users tab enables you to add a single user to multiple application roles. You can also view the roles and application roles that a user belongs to. This shows roles from the identity domain associated with your service. Roles cannot be added or changed through Oracle BI Cloud Service but they can be added as members to application roles. The Roles tab enables you to add a single role to multiple application roles. You can also view which users are members of a role and see which other roles and application roles that a role belongs to. This enables you to manage predefined and user-defined application roles. The Application Roles tab enables you to add multiple users, roles, and application roles as members of an application role. You can also choose the parent application roles an application role inherits privileges from. 20-4 Using Oracle Business Intelligence Cloud Service

Configuring What Users Can See and Do Assigning Members and Actions to Application Roles Administrators can use the Applications Role page to modify the display name of a user-defined application role to be more user-friendly. You can also select users, roles, and application roles to be members or parents of an application role. For more information, see About Application Roles. To select members (users, roles, and other application roles) for an application role or change parent privileges for an application role: Note: Members inherit the privileges of the application role, and an application role inherits privileges from its parents. 1. From the Application Role Management tab, select Application Roles. 2. To see all available application roles, leave the Name filter blank and click Search. Alternatively, enter a partial or complete application role name in the Name filter, and click Search. The search is case-insensitive, and searches both name and display name. 3. Select an application role in the results table. Optionally, click Edit Application Role to update names and descriptions for userdefined application roles. 4. To see current members, click the Members of tab. The members listed gain all the permissions that are granted to the application role. 5. Click Edit members. 6. In the Edit members of dialog, perform the following steps for each type of member (users, roles, and application roles): a. In the Type box, select from users, roles, or application roles. Managing What Users Can See and Do 20-5

Configuring What Users Can See and Do b. Enter a partial or complete name of a member, and click Search. c. Use the shuttle controls to move members between the Available and All Selected list. You cannot add all application roles as members. Items that you cannot add are displayed in grey. For example, you cannot add parents as members Note: Users marked absent" no longer have an account in the identity domain. To remove absent users, use the shuttle control to move the user from the "All selected users" list to the "Available users" list. d. Click OK. 7. To see current parents, select the Parents of tab. The application role inherits privileges from all the parents listed here. 8. Click Edit parents to add or remove privileges for an application role. 9. Select parent application roles: a. Enter a partial or complete application role name and click Search. b. Use the shuttle controls to move application roles between the Available parents list and the All selected parents list. Like Edit Members, you cannot select application roles as parents if they create a circular membership tree. The Description field shows a description of the item. If you select multiple items, then you see the description for the last item that you selected. c. Click OK. Why is Membership of the BI Service Administrator Application Role Important? You must be a member of the BI Service Administrator application role to use the Service Console. If you remove your own membership from the BI Service Administrator application role, then you see a warning message because there must always be at least one user who has this application role. If you remove your own membership, you can continue to use the Service Console in the current session but you can t use the Service Console in the future. To continue to use the Service Console, you must reinstate your membership during the current session. No Users With the BI Service Administrator Application Role? If no one has access to the Service Console, ask your identity domain administrator to add you or another user to the <serviceinstancename>.bicloudserviceadministrator role through My Services Security. This role is a member of the predefined application role BI Service Administrator and enables access to the Service Console. 20-6 Using Oracle Business Intelligence Cloud Service

Configuring What Users Can See and Do Assigning Application Roles to Users The Users page shows users from the identity domain associated with your Oracle BI Cloud Service. Users cannot be added or changed through the Oracle BI Cloud Service but you can assign them to one or more application roles. The Users page enables you to add a single user to multiple application roles and to view the roles and application roles that a user is a direct member of. To manage application role memberships for users: 1. From the Application Role Management tab, select Users. 2. In the Name filter field, enter a partial or complete user name, and click Search. Search is by "contains," is case-insensitive and searches both the name and display name. If you leave the field empty, then all users are displayed. 3. Select a user in the table. Two tabs display: Tab Name Parent roles of Parent application roles of Description Lists the roles that the selected role is a direct member of. Lists the application roles that the selected role is a direct member of. Membership of application roles gives the role (and in turn its members) permissions in Oracle BI Cloud Service. 4. Display the Parent application roles of tab. 5. Click Edit parents. 6. Search for the application roles that you want to add or remove for the user. 7. Use the shuttle controls to move application roles between the Available parents list and the All selected parents list. 8. Click OK. Assigning Application Roles to User Roles The Roles page shows roles from the identity domain associated with your Oracle BI Cloud Service. Roles cannot be added or changed through Oracle BI Cloud Service but you can assign them one or more application roles. The Roles tab enables you to add a single role to multiple application roles. You can also view which users are members of a role and see which other roles and application roles that a role belongs to. Managing What Users Can See and Do 20-7

Configuring What Users Can See and Do To view and edit roles: 1. From the Application Role Management tab, select Roles. 2. In the Name filter field, enter a partial or complete role name, and click Search. Search is by "contains," is case-insensitive, and searches both name and display name. If you leave the field empty, then all roles display. 3. Select the role you want to edit. 4. Select either the Members of, Parent roles of, or Parent application roles of tab. Tab Name Members of Parent roles of Parent application roles of Description Lists direct user and role members of the selected role (that is, lists its children). Lists the parent roles that the selected role is a direct member of. Lists the parent application roles that the selected role is a direct member of. Membership of application roles gives the role (and in turn its members) permissions in Oracle BI Cloud Service. 5. From the Parent application roles of tab, click Edit parents. 6. Search for the application roles that you want to add for the role. 7. Use the shuttle controls to move application roles between the Available parents list and the All selected parents list. 8. Click OK. Adding Your Own Application Roles Oracle BI Cloud Service provides a set of predefined application roles, but you can also create application roles of your own to suit your business. Administrators can use the Applications Role page to create user-defined application roles, add members, and specify parent application roles. For example, you can create a user-defined application role that allows users to view folders and reports or an application role that restricts access to specific parts of the data model. To create a user-defined application role: 1. On the Home page, click Manage. 20-8 Using Oracle Business Intelligence Cloud Service

Configuring What Users Can See and Do 2. From the Application Role Management tab, select Application Roles. 3. Click Create application role. Exiting the Service Console 4. Enter a name, describe the application role, and click Save. 5. Select the newly created application role. 6. Add members and parents to the application role, as described in Assigning Members and Actions to Application Roles. When you finish working in the Service Console, click Sign Out in the upper-right corner. If you click Back on the browser while working in the console, you exit the console but you are not signed out. This means that if you press Back, then Forward, you return to the console. Deleting Application Roles You can use the Applications Role page to delete an application role that you created but no longer need. To delete a user-defined application role: 1. From the Application Role Management tab, select Application Roles. 2. To display the application role you want to delete, enter a partial or complete application role name in the Name filter, and click Search. 3. Select an application role in the table. 4. Click Delete application role. Managing What Users Can See and Do 20-9

Functionality Enabled by Application Roles 5. Click OK. Functionality Enabled by Application Roles Application roles determine what you can see and do in Oracle BI Cloud Service. This topic describes what you are allowed to see and do with the predefined application roles. Information is organized in two ways: Application role by functionality Functionality by application role Application Role by Functionality Feature Functionality in Oracle BI Cloud Service Application Role Access Access to Data Loader BI Data Model Author Access Access to Data Modeler BI Data Model Author Access Access Access to Oracle BI Cloud Service Data Sync Access to Oracle BI Cloud Service REST API BI Data Load Author BI Data Load Author Access Access to Dashboards BI Consumer Access Access to Catalog Preview Pane BI Consumer Access Access to Export BI Advanced Content Author Access Access to Metadata Dictionary BI Content Author Access Access to Mobile BI Consumer Access Access Add Data Sources for Analyses and Dashboards Add Data Sources for Visual Analyzer Projects BI Advanced Content Author BI Discovery Content Author Access Create or Edit Analyses BI Content Author Access Create or Edit Analyses with Accessibility Option Enabled BI Content Author Actions Create or Edit Navigate Actions BI Advanced Content Author Actions Create or Edit Visual Analyzer Projects BI Discovery Content Author Admin: Catalog Change Permissions BI Content Author Admin: Connection Change Database Connection BI Service Administrator Admin: General Manage Session Information BI Service Administrator Admin: General Manage Dashboards BI Content Author Admin: Security Manage Application Roles BI Service Administrator Admin: Security Set Ownership of Catalog Objects BI Service Administrator Admin: Security Access to Application Role Management BI Consumer Admin: Security Users/Roles - Can List Users and Roles BI Consumer 20-10 Using Oracle Business Intelligence Cloud Service

Functionality Enabled by Application Roles Feature Functionality in Oracle BI Cloud Service Application Role Admin: Security Admin: Snapshots Admin: Snapshots Catalog Application Roles - Can List Application Roles Back up and Restore with Snapshots Upload Data Model from a File (.rpd) Personal Storage My Folders and My Dashboard BI Consumer BI Service Administrator BI Service Administrator BI Consumer Catalog Reload Server Metadata BI Service Administrator BI Data Model Author Catalog See Hidden Items BI Content Author Catalog Create Folders BI Content Author Catalog Archive Catalog BI Service Administrator Catalog Unarchive Catalog BI Service Administrator Catalog Perform Global Search BI Content Author Conditions Create Conditions BI Content Author Dashboards Save Customizations BI Consumer Dashboards Assign Default Customizations BI Content Author Dashboards Create Bookmark Links BI Consumer Dashboards Export Entire Dashboard to Excel BI Advanced Content Author Dashboards Export Single Dashboard Page to Excel BI Advanced Content Author Home and Header Home and Header Home and Header Home and Header Home and Header Home and Header Home and Header Home and Header Home and Header Access Home Page Access Catalog UI Access Catalog Search UI Simple Search Field Open Menu New Menu Help Menu Dashboards Menu Favorites Menu BI Consumer BI Consumer BI Consumer BI Consumer BI Consumer BI Consumer BI Consumer BI Consumer BI Consumer Managing What Users Can See and Do 20-11

Functionality Enabled by Application Roles Feature Home and Header Functionality in Oracle BI Cloud Service My Account Link Application Role BI Consumer My Account Access to My Account BI Consumer My Account Change Preferences BI Consumer Analysis Add Data Source BI Advanced Content Author Analysis Create Views BI Content Author Analysis Create Prompts BI Content Author Analysis Edit Column Formulas BI Content Author Analysis Edit Column Formulas BI Content Author Analysis Create Advanced Filters and Set Operations BI Content Author Answers Save Filters BI Content Author Mobile Enable Local Content BI Consumer Mobile Enable Search BI Consumer Subject Area Create and Edit Analyses BI Content Author View Column Selector View Compound Layout Add/Edit Column SelectorView Add/Edit Compound LayoutView BI Content Author BI Content Author View Graph Add/Edit GraphView BI Content Author View Funnel Add/Edit FunnelView BI Content Author View Gauge Add/Edit GaugeView BI Content Author View Micro Chart Add/Edit Micro Chart View BI Content Author View Filters Add/Edit FiltersView BI Content Author View Dashboard Prompt View Performance Tile Add/Edit Dashboard PromptView Add/Edit Performance TileView BI Content Author BI Content Author View Static Text Add/Edit Static TextView BI Content Author View Narrative Add/Edit NarrativeView BI Content Author View No Results Add/Edit No ResultsView BI Content Author View Pivot Table Add/Edit Pivot TableView BI Content Author View Report Prompt View Selection Steps View Logical SQL Add/Edit Report PromptView Add/Edit Selection StepsView Add/Edit Logical SQLView BI Content Author BI Content Author BI Content Author 20-12 Using Oracle Business Intelligence Cloud Service

Functionality Enabled by Application Roles Feature Functionality in Oracle BI Cloud Service Application Role View Table Add/Edit TableView BI Content Author View Title Add/Edit TitleView BI Content Author View Treemap Add/Edit TreemapView BI Content Author View Trellis Add/Edit TrellisView BI Content Author View View Selector Add/Edit View SelectorView BI Content Author Functionality by Application Role Application Role Functionality in Oracle BI Cloud Service Feature BI Consumer Access to Dashboards Access BI Consumer Access to Mobile Access BI Consumer Access to Catalog Preview Pane Access BI Consumer Personal Storage - My Folders and My Dashboard Catalog BI Consumer Save Customizations Dashboards BI Consumer Create Bookmark Links Dashboards BI Consumer Access Home Page Home and Header BI Consumer Access Catalog UI Home and Header BI Consumer Access Catalog Search UI Home and Header BI Consumer Simple Search Field Home and Header BI Consumer Open Menu Home and Header BI Consumer New Menu Home and Header BI Consumer Help Menu Home and Header BI Consumer Dashboards Menu Home and Header BI Consumer Favorites Menu Home and Header BI Consumer My Account Link Home and Header BI Consumer Access to My Account My Account BI Consumer Change Preferences My Account BI Consumer Enable Local Content Mobile Managing What Users Can See and Do 20-13

Functionality Enabled by Application Roles Application Role Functionality in Oracle BI Cloud Service Feature BI Consumer Enable Search Mobile BI Content Author Create and Edit Analyses Access BI Content Author Create or Edit Analyses with Accessibility Option Enabled Access BI Content Author Access to Metadata Dictionary Access BI Content Author Change Permissions Admin: Catalog BI Content Author Manage Dashboards Admin: General BI Content Author See Hidden Items Catalog BI Content Author Create Folders Catalog BI Content Author Perform Global Search Catalog BI Content Author Create Conditions Conditions BI Content Author Assign Default Customizations Dashboards BI Content Author Create Views Analysis BI Content Author Create Prompts Analysis BI Content Author Edit Column Formulas Analysis BI Content Author Edit Column Formulas Analysis BI Content Author Create Advanced Filters and Set Operations Analysis BI Content Author Save Filters Answers BI Content Author Create and Edit Analyses Subject Area BI Content Author Add/Edit Column SelectorView View Column Selector BI Content Author Add/Edit Compound LayoutView View Compound Layout BI Content Author Add/Edit GraphView View Graph BI Content Author Add/Edit FunnelView View Funnel BI Content Author Add/Edit GaugeView View Gauge BI Content Author Add/Edit Micro Chart View View Micro Chart BI Content Author Add/Edit FiltersView View Filters BI Content Author Add/Edit Dashboard PromptView View Dashboard Prompt BI Content Author Add/Edit Performance TileView View Performance Tile BI Content Author Add/Edit Static TextView View Static Text BI Content Author Add/Edit NarrativeView View Narrative BI Content Author Add/Edit No ResultsView View No Results BI Content Author Add/Edit Pivot TableView View Pivot Table 20-14 Using Oracle Business Intelligence Cloud Service

Functionality Enabled by Application Roles Application Role Functionality in Oracle BI Cloud Service Feature BI Content Author Add/Edit Report PromptView View Report Prompt BI Content Author Add/Edit Selection StepsView View Selection Steps BI Content Author Add/Edit Logical SQLView View Logical SQL BI Content Author Add/Edit TableView View Table BI Content Author Add/Edit TitleView View Title BI Content Author Add/Edit TreemapView View Treemap BI Content Author Add/Edit TrellisView View Trellis BI Content Author Add/Edit View SelectorView View View Selector BI Content Author Add/Edit View SelectorView View View Selector BI Discovery Content Author Add Data Sources for Visual Analyzer Projects Access BI Advanced Content Author Access to Export Access BI Advanced Content Author Create Navigate Actions Actions BI Advanced Content Author Add Data Sources for Analyses and Dashboards Access BI Advanced Content Author Export Entire Dashboard to Excel Dashboards BI Advanced Content Author Export Single Dashboard Page to Excel Dashboards BI Data Load Author BI Data Load Author Access to Oracle BI Cloud Service Data Sync Access to Oracle BI Cloud Service REST API Access Access BI Data Model Author Access to Data Loader Access BI Data Model Author Access to Data Modeler Access BI Data Model Author Reload Server Metadata Catalog BI Service Administrator Change Database Connection Admin: Connection BI Service Administrator Manage Session Information Admin: General BI Service Administrator Manage Application Roles Admin: Security BI Service Administrator Set Ownership of Catalog Objects Admin: Security BI Service Administrator Backup and Restore with Snapshots Admin: Snapshots BI Service Administrator Upload a Data Model from a File (.rpd) Admin: Snapshots BI Service Administrator Reload Server Metadata Catalog Managing What Users Can See and Do 20-15

Functionality Enabled by Application Roles Application Role Functionality in Oracle BI Cloud Service Feature BI Service Administrator Archive Catalog Catalog BI Service Administrator Unarchive Catalog Catalog 20-16 Using Oracle Business Intelligence Cloud Service

21 Backing Up and Restoring This topic describes how to back up and restore the data model, catalog content, and application roles for Oracle BI Cloud Service using a file called a snapshot. Topics: Typical Workflow for Backing Up and Restoring About Snapshots Taking Snapshots and Restoring Information Downloading, Uploading, and Migrating Snapshots Typical Workflow for Backing Up and Restoring Here are the common tasks to back up and restore the system using snapshots. Task Description More Information Take a snapshot Restore from a snapshot Capture the data model, catalog, and application roles in Oracle BI Cloud Service at a point in time. Restore the data model, catalog, and application roles to a previously working state. Taking a Snapshot Restoring from a Snapshot Delete a snapshot Delete unwanted snapshot. Deleting Snapshots Download a snapshot Upload a snapshot Migrate snapshot data Save a snapshot to a local file system. Upload a snapshot stored on a local file system to Oracle BI Cloud Service. Migrate data models, catalog content, and application roles. Downloading Snapshots Uploading Snapshots Migrating Snapshot Data About Snapshots A snapshot captures the state your Oracle BI Cloud Service at a point in time and includes the data model, catalog content, and application roles. Artifacts Saved In a Snapshot Data model Catalog Description A snapshot of the data model created using Data Modeler. A snapshot of the catalog that contains things saved for future use (such as analyses and dashboards). Backing Up and Restoring 21-1

Taking Snapshots and Restoring Information Artifacts Saved In a Snapshot Application roles Description A snapshot of the application role definitions defined for your Oracle BI Cloud Service. You can download a snapshot to a file system and upload a saved snapshot from a file system (of the same service that created the snapshot). This feature is useful if you want to move data from a development or test environment to a production Oracle BI Cloud Service. You can keep up to 10 snapshots online but download as many as you want. Taking Snapshots and Restoring Information You can take a snapshot of your Oracle BI Cloud Service at any time. Video Taking a Snapshot Topics: Taking a Snapshot Restoring from a Snapshot Editing Snapshot Descriptions Deleting Snapshots Administrators can take a snapshot of Oracle BI Cloud Service at any time. To take a snapshot: 1. On the Home page, click Manage. 2. Select the Snapshots tab, and click New Snapshot. 3. Enter a short description for the snapshot to help you remember later why you took it. For example, why you created the snapshot and what it contains. 4. Click OK. 21-2 Using Oracle Business Intelligence Cloud Service

Taking Snapshots and Restoring Information The latest data model, catalog, and application role definitions are saved in a snapshot and a message displays at the top right hand side of the page. Restoring from a Snapshot If something goes wrong because of a change to the data model, catalog, or application roles, it s easy to restore Oracle BI Cloud Service to a previous working state from a snapshot. Note: Restoring from a snapshot overwrites the data model, catalog, and application roles (if selected for restore) to a previous state and any user sessions are terminated. To restore from a snapshot: 1. From the Snapshots tab, select the snapshot that you want to use to restore your Oracle BI Cloud Service. 2. Click Manage Snapshot. 3. Click Restore to return Oracle BI Cloud Service to the state when this snapshot was taken. 4. In the Restore Snapshot dialog, select all the elements you want to restore. You can select one or more from data model, catalog, and application roles. By default Oracle BI Cloud Service restores everything but you can choose to only restore certain snapshot elements. For example, if you are restoring a snapshot from a pre-production service to a production service you may not want to include application roles. Pre-production roles often have different members to the production service. If so, deselect Application Roles before clicking Restore. Backing Up and Restoring 21-3

Taking Snapshots and Restoring Information 5. Click Restore. A warning message displays because restoring a snapshot can be very disruptive. 6. Click Yes to restore the selected snapshot, or click No to abandon the restore. Editing Snapshot Descriptions You can add or update descriptions for any snapshot. To edit a snapshot description: 1. From the Snapshots tab, select the snapshot you want to edit. 2. Click Manage Snapshot. Deleting Snapshots 3. Click Edit to update the description. 4. Update the description, and click OK. From time to time, delete snapshots that you do not need. To delete a snapshot: 1. From the Snapshots tab, select the snapshot that you want to delete. 21-4 Using Oracle Business Intelligence Cloud Service

Downloading, Uploading, and Migrating Snapshots 2. Click Manage Snapshot. 3. Click Delete to delete the snapshot. A message displays at the top right hand side of the page. If you change your mind, click Undo. Downloading, Uploading, and Migrating Snapshots Download and upload features enable you to save snapshots of your Oracle BI Cloud Service to your local file system, and upload them to the Cloud. Use these features to back up and restore service data and to migrate data from one Oracle BI Cloud Service to another. Video Topics: Downloading Snapshots Downloading Snapshots Uploading Snapshots Migrating Snapshot Data Use the Download option in the Snapshots tab to save a snapshot to your local file system. For example, you can locally store and manage snapshots taken of your Oracle BI Cloud Service. If you haven't taken the snapshot yet, you ll need to do that first. See Taking a Snapshot. To download a snapshot: 1. From the Snapshots tab, select the snapshot that you want to download. 2. Click Manage Snapshot. Backing Up and Restoring 21-5

Downloading, Uploading, and Migrating Snapshots 3. Click Download. 4. Enter and confirm a new password for this snapshot. The password must contain at least 8 characters. You must remember this password, because you enter it again during the upload process. 5. Click OK. Uploading Snapshots What happens next depends on your browser. In Internet Explorer, for example, you browse the Save As dialog, and click Save to save the snapshot in the selected location. The snapshot downloads as an Oracle Business Intelligence archive file (.bar). Oracle BI Cloud Service artifacts (data model, catalog, and application roles) are included in the archive. You upload a snapshot of Oracle BI Cloud Service using the Snapshots tab in the Service Console. For example, you may upload a snapshot when moving artifacts created in a test environment to a production environment. When you upload a snapshot, artifacts stored inside the snapshot are not immediately available in your Oracle BI Cloud Service. After upload, your snapshot displays in the snapshot list. When you are ready to do so, you can overwrite the current data model, catalog, or application roles with those stored in the snapshot. See Restoring from a Snapshot. To upload a snapshot: 1. From the Snapshots tab, click Upload Snapshot. 2. Use Browse to locate the snapshot that you want to upload. Choose the Oracle Business Intelligence archive file (.bar) that contains your snapshot. 3. Enter the snapshot password. You set the password during the download process. 4. Click OK. The uploaded snapshot is displayed in the list of saved snapshots. Follow steps in Restoring from a Snapshot to restore the snapshot that you just uploaded. 21-6 Using Oracle Business Intelligence Cloud Service

Downloading, Uploading, and Migrating Snapshots Migrating Snapshot Data You can migrate the data model, catalog content, and application roles created in one Oracle BI Cloud Service environment to another, using snapshots. For example, you may want to move pre-production data to a production service. To migrate snapshot data to another Oracle BI Cloud Service: 1. Download the snapshot that you want to migrate to your local file system. See Downloading Snapshots. 2. Sign in to the target Oracle BI Cloud Service, and upload the snapshot. See Uploading Snapshots. 3. Select the newly uploaded snapshot from the list of saved snapshots. Follow steps in Restoring from a Snapshot to migrate the data model, catalog, or application roles saved in the snapshot to the target Oracle BI Cloud Service. Backing Up and Restoring 21-7

22 Performing Administration Tasks This topic describes tasks performed by administrators managing Oracle BI Cloud Service. Topics: Typical Workflow for Performing Administration Tasks Understanding Administration Tools Changing the Database Connection Uploading Data Models from a File (.rpd) Managing Session Information in Oracle BI Cloud Service Executing Test SQL Queries Monitoring Metrics for Oracle BI Cloud Service Typical Workflow for Performing Administration Tasks Here are the common tasks for administration. Task Description More Information Manage what users see and do Back up and restore content Change the database connection Manage session information Monitor metrics Configure what users see and do in Oracle BI Cloud Service using the Application Role Management page. Back up and restore the data model, catalog content, and application roles using a file called a snapshot. Connect Oracle BI Cloud Service to a different cloud database. Monitor who is signed in and troubleshoot issues with analyses by analyzing the SQL queries and logs. Monitor metrics for Oracle BI Cloud Service. Managing What Users Can See and Do Backing Up and Restoring Changing the Database Connection Managing Session Information in Oracle BI Cloud Service Monitoring Metrics for Oracle BI Cloud Service Performing Administration Tasks 22-1

Understanding Administration Tools Understanding Administration Tools You administer Oracle BI Cloud Service from the Oracle BI Cloud Service Home page, Oracle BI Cloud Service - Service Console, and Oracle Cloud - My Services. Tool Name Oracle BI Cloud Service - Home page Oracle BI Cloud Service - Service Console Oracle Cloud - My Services Description and How to Access See who is currently signed in, diagnose issues with SQL queries, and open the Service Console. Access these administrative options from the Administration menu in Oracle BI Cloud Service. See Managing Session Information in Oracle BI Cloud Service and Executing Test SQL Queries. Manage user permissions, back up your information, and change the database connection. Access the Service Console either by clicking Manage on the Home page or User and Role Admin from the Administration menu. See Managing What Users Can See and Do, Backing Up and Restoring, and Changing the Database Connection. Monitor metrics. Access usage and other metrics using Oracle Cloud. See Monitoring Metrics for Oracle BI Cloud Service. You must have the BI Service Administrator role to perform all the administration tasks outlined here. Changing the Database Connection Change database connection information for Oracle BI Cloud Service if you want to build data models and analyze data stored in a different Oracle Database Cloud Service. When you integrate Oracle BI Cloud Service with a different database service, existing content such as, model objects, reports, and dashboards, continue to work providing that all the required source objects are available in the new database. See also How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service? To change and test the database connection: 1. On the Home page, click Manage. 2. Select the Database Connection tab. 3. Select Use a different cloud database to connect Oracle BI Cloud Service to an Oracle Database Cloud Service (Database as a Service) instance. Tip: The option Use the database included with your service connects to Oracle Database Cloud Service (Database Schema) packaged with your Oracle BI Cloud Service. 4. Enter database connection information. 22-2 Using Oracle Business Intelligence Cloud Service

Uploading Data Models from a File (.rpd) The target database must be Oracle Database Cloud Service (Database as a Service). Ask the database administrator to provide the connection information. Note: You don't need to enter database information on the Database Connection tab if you ve chosen to upload data models built with Oracle BI Enterprise Edition because connection information is defined in the data model file (.rpd) that you upload to Oracle BI Cloud Service. See About Uploading Data Models to the Cloud. Option Host Port SID Connect as Password Description Address of the database server or the host s name. Port number on which the database server is listening for incoming connections. Name of the Oracle database instance. Name of a database user. User s password to access the database. 5. Click Test to verify the connection. 6. Click Save Connection information to save your settings. Uploading Data Models from a File (.rpd) Administrators can upload data models built with Oracle BI Enterprise Edition to Oracle BI Cloud Service. After uploading a data model file (.rpd) to the cloud, content authors can build analyses and dashboards in the usual way. Tutorial Topics About Uploading Data Models to the Cloud Uploading Data Models to the Cloud About Uploading Data Models to the Cloud If you ve modeled your business data with Oracle BI Enterprise Edition you don't need to start from scratch in Oracle BI Cloud Service. Simply upload your data model file (.rpd) to Oracle BI Cloud Service and start exploring your data through visualizations, analyses, and dashboards. Oracle BI Cloud Service lets you upload a data model file (.rpd) with: One or more data model Connections to one or more Oracle Database Cloud Service (Database as a Service) You ll need to validate your data model file and configure database connection details in Oracle BI Enterprise Edition. Performing Administration Tasks 22-3

Uploading Data Models from a File (.rpd) Getting Your Data Model File Ready for the Cloud Take some time to ready your data model file (.rpd) for the cloud: Verify that you re using Oracle BI Enterprise Edition 11.1.1.6 or later Validate the data model file Run consistency checks using Consistency Check Manager in Oracle BI Administration Tool. Verify that the data model file includes connection details to an Oracle Cloud database Review connection pool settings from Oracle BI Administration Tool: Data source name must point to the Oracle Database Cloud Service (Database as a Service) instance where the data is stored. Call interface must be Oracle Call Interface (OCI). If your data model file contains connections to multiple Oracle Database Cloud Service (Database as a Service) instances, check connection pool settings one-byone. When your data model file (.rpd) is ready you can upload it to Oracle BI Cloud Service. Before doing so, we recommend that you back up your current data model in case you need to restore this version. See Uploading Data Models to the Cloud. During the upload, existing data model information in Oracle BI Cloud Service is deleted and replaced with content from the uploaded file. Data models uploaded from the file become available to content authors through the Subject Areas pane. Editing Data Models Uploaded to the Cloud You can t edit data models created with Oracle BI Enterprise Edition through Oracle BI Cloud Service. Data Modeler is disabled when you upload data models to Oracle BI Cloud Service from an RPD file. If you want to improve or update the model, make your updates in Oracle BI Administration Tool, re-run consistency checks, and upload the data model file again. Each time that you upload a data model, you delete and replace the existing model with the newly uploaded content. Tip: Model changes, such as deleting columns from the model, may affect existing content so take some time to check existing analyses and dashboards after uploading model updates. 22-4 Using Oracle Business Intelligence Cloud Service

Uploading Data Models from a File (.rpd) Uploading Data Models to the Cloud Administrators can upload data models built with Oracle BI Enterprise Edition to Oracle BI Cloud Service. After migrating data models to the cloud, content authors can visualize data in the usual way. When you upload data models from Oracle BI Enterprise Edition, you delete existing data model information in Oracle BI Cloud Service and replace it with content in the data model file (.rpd). The data models you upload become available to content authors through the Subject Areas pane. To upload data models created with Oracle BI Enterprise Edition to the cloud: 1. Verify the data model file (.rpd) and database connections. See About Uploading Data Models to the Cloud. 2. On the Home page, click Manage. 3. Select the Snapshots tab. 4. Take a snapshot of the current data model in case you need to restore this version. See Taking a Snapshot. 5. Click Replace Data Model. 6. Click Browse and select the data model file (.rpd) you want to upload. 7. Enter the password for the file. 8. Click OK. 9. Go to the Home page, and click Create an Analysis to see the data models in Oracle BI Cloud Service. Data models you uploaded from the file display in the Subject Areas pane. 10. Optional. If the data model file you uploaded defines permissions and data filters, create matching application roles in Oracle BI Cloud Service for the data security to work in the cloud. a. Create application roles with exactly the same names as those defined in Oracle BI Administration Tool. See Adding Your Own Application Roles. b. Assign users (and user roles) to the application roles as required. See Assigning Application Roles to Users and Assigning Application Roles to User Roles. Performing Administration Tasks 22-5

Managing Session Information in Oracle BI Cloud Service Managing Session Information in Oracle BI Cloud Service You can see information about users who are signed to Oracle BI Cloud Service from the Manage Session page. Topics: Monitoring Users Who Are Signed In Analyzing SQL Queries and Logs Monitoring Users Who Are Signed In You can see how many users are signed in to Oracle BI Cloud Service and view detailed information about each user from the Manage Session page. To monitor users who are signed in: 1. On the Home page, select Administration, then Manage Sessions. The Sessions section at the top of the page shows how many users are currently signed in (Total Number of Sessions). The table provides details about the users who are signed in to Oracle BI Cloud Service: Field User ID Session ID Browser Info Logged On Last Access Description The name that the user entered when they signed in. A unique identifier assigned by Oracle BI Cloud Service for each user session. Information about the browser from which the user signed on. The time stamp when the user signed in. The time stamp of the last activity for this user on Oracle BI Cloud Service. This can be any kind of activity, such as switching from one dashboard page to another. 2. To monitor a particular user, select Filter Cursors by Session. Information for this user displays in the Cursor Cache table. See Analyzing SQL Queries and Logs. Click Clear Filter to show information for all users. 3. To change how messages are logged for a particular user, select a Log Level from the list. By default, logging is disabled. Analyzing SQL Queries and Logs You can view SQL query requests made by users from the Manage Session page. To examine SQL queries and logs relating to user activity: 1. On the Home page, select Administration, then Manage Sessions. 22-6 Using Oracle Business Intelligence Cloud Service

Managing Session Information in Oracle BI Cloud Service The Cursor Cache section enables you to monitor and troubleshoot activity logs for users currently signed in to Oracle BI Cloud Service. Field ID User Refs Status Time Action Last Accessed Statement Information Records Description A unique internal identifier that is assigned to each entry. The name of the user who ran the analysis and last placed it into the cache. The number of references to this entry since it was placed into the cache. The status of the analysis that is using this cache entry: Starting The analysis is starting to run. Waiting on Parent A view in the analysis is waiting for the Oracle BI Server to finish returning the data for the query. Running The analysis is currently running. Finished The analysis has finished. Queued The system is waiting for a thread to become available so the analysis can be processed. Canceling The application is in the process of canceling the analysis. Error An error occurred during the processing or running of the analysis. Look in the Statement column for information about the error. The time taken to process and run the analysis, displayed in one-second increments. A value of 0s (zero seconds) indicates that the analysis took under 1 second to complete. Links that you can click to affect the analysis: Cancel Terminates the analysis. Is displayed for in-progress analyses. The user running the analysis receives an informational message indicating that the analysis was canceled by an administrator. Close Clears the cache entry associated with this analysis. Is displayed for completed analyses. View Log Displays the log of a query executed for this analysis. Diagnostic Displays an HTML page of diagnostic information that you can share with Oracle Customer Support. The time stamp of the last time the cache entry for this analysis was used to satisfy an analysis. The SQL statement that was issued for the analysis; or if the analysis resulted in an error, information about the nature of the error. Usage tracking information (for example, what analysis contained the query). The number of records in the result set that have been seen (for example, 50+ to indicate that 50 records have been seen but there are additional records to be fetched or 75 to indicate that 75 records have been seen and there are no more records to be fetched). 2. Optionally click Close All Cursors to removes information in the Cursor Cache table. 3. Optionally click Cancel Running Requests to cancel all requests that are running for analyses. Performing Administration Tasks 22-7

Executing Test SQL Queries Executing Test SQL Queries Administrators can enter a SQL statement directly to underlying data sources. This feature is useful for testing purposes. Results are not formatted, and you cannot save SQL statements that you issue directly. Not all SQL functions and procedures are supported, such as the NQSSetSessionVariables() procedure. To execute test SQL statements: 1. Sign in to Oracle BI Cloud Service. 2. From the Administration link on the Home page, select Issue SQL. 3. Enter the SQL statement. 4. Change the Logging Level if required. Each user receives a default logging level. Select Default in this box to use your default level. 5. Specify whether to run the query against cached data. Deselect Use Oracle BI Presentation Services Cache to specify that you do not want the query to use cached data. In general, avoid deselecting this box as disabling the cache has potential performance degradation issues. 6. Click Issue SQL. Monitoring Metrics for Oracle BI Cloud Service Administrators can view status and track usage metrics for Oracle BI Cloud Service from My Services. From My Services you can see whether Oracle BI Cloud Service and its associated Oracle Database Cloud Service are available and working as expected (Up). See also, How Does Oracle BI Cloud Service Integrate with Oracle Database Cloud Service? You can also track how many people are using Oracle BI Cloud Service by their role: BI Consumers This Month Reports how many of the people who signed in to Oracle BI Cloud Service during the current calendar month can view and run analyses (have the BI Consumer application role). BI Authors This Month Reports how many of the people who signed in to Oracle BI Cloud Service during the current calendar month can create analyses and dashboards (have the BI Content Author application role) or perform advanced content management tasks, such as exporting dashboards (have the BI Advance Content Author application role). BI Author Modelers This Month Reports how many of the people who signed in to Oracle BI Cloud Service during the current calendar month can model data and load data using Data Loader (have the BI Data Model Author application role). BI Admins This Month Reports how many of the people who signed in to Oracle BI Cloud Service during the current calendar month can administer Oracle BI Cloud Service and delegate privileges to others (have the BI Service Administrator application role). 22-8 Using Oracle Business Intelligence Cloud Service

Monitoring Metrics for Oracle BI Cloud Service For more information, see Viewing Service Details in My Services in Getting Started with Oracle Cloud. Performing Administration Tasks 22-9

Part VII Reference This part provides reference information for Oracle BI Cloud Service. Appendices: Terminology Frequently Asked Questions for Oracle Business Intelligence Cloud Service Troubleshooting Oracle Business Intelligence Cloud Service Expression Editor Reference Accessibility

A Terminology Here are some Oracle BI Cloud Service terms that are used in this book. Term action action link analysis application role attribute briefing book calculated item calculated measure canvas Definition An action enables you to navigate to related content or a web page. You can include actions in analyses and dashboard pages. For example, you can use an action in the Brand Revenue analysis to enable sales consultants to navigate to an Opportunity Detail web site. An action link enables you to embed a link to an action in an analysis or dashboard page, that, when clicked, runs an associated action. For example, you can embed an action link in the Brand Revenue analysis to enable sales consultants to navigate to an Opportunity Detail web site. An analysis provides answers to business questions by querying against your organization's data. Analyses enable you to explore and interact with information by visually presenting data in tables, graphs, pivot tables, and to save, organize, and share the results of analyses. For example, you can create a Brand Revenue analysis that shows data in views on a Sales Performance dashboard. You can share this analysis with co-workers, clients, and business partners. An application role comprises a set of privileges that determine what users can see and do in Oracle BI Cloud Service. In Oracle BI Cloud Service, you associate users or roles configured in your identity domain with one or more application roles. The users and roles inherit their privileges in Oracle BI Cloud Service from these application roles. Attributes are member-based data items that can be used as simple categories or arranged as hierarchies with levels. Contrast an attribute with a measure. You can store a static snapshot of dashboard pages or individual analyses in one or more briefing books. You can also configure a briefing book to refresh data when accessed. For example, as a sales representative, you can use a briefing book to collect a snapshot of a Sales Performance analysis each quarter. A calculated item shows you a calculation between members, which is represented as a single member. A calculated item is useful when you want to view and manipulate a set of members as a single entity. For example, as a sales analyst, you can create a member in the Fulfillment by Quarter analysis that shows the average revenue for the Game Station and Plasma Television members. In the data model, calculated measures are columns in tables that are derived from other measures and based on expressions. For example, a calculated measure called Unit Price might be based on the expression Revenue / Billed Units. The location for visualizations in a Visual Analyzer project. Terminology A-1

Term catalog column dashboard Data Loader Data Modeler derived attribute dimension table fact table filter Definition The catalog contains things that you or somebody else has defined and saved for future use (such as projects, analyses, and dashboards). You can search the catalog to find something that you want to work with or change. For example, you might want to edit an analysis in a shared folder in the catalog. Permissions control the access and sharing of items in the catalog. Similar to database columns, Oracle BI Cloud Service has the concept of a column. In Oracle BI Cloud Service, columns are used in different contexts. A column in an analysis is based on a column, a derived attribute, or a calculated measure that was defined in Data Modeler. Columns in Data Modeler, in turn, are based on source columns in Oracle Database Cloud Service. In an analysis or project, columns indicate the pieces of data that you want to display. You can use columns, along with filters (and selection steps in analyses), to determine what analyses and projects contain. Columns have names that indicate to you the types of information that they contain. For example, you can use columns named Account and Contact to display information in an visualizations. In visualizations, such as a pivot table and trellis, columns are vertical arrangements of data. For example, a pivot table can include a column of Revenue data. A dashboard shows information that is relevant to you and consists of one or more pages. Each page can present information in different ways, such as graphs, tables, and images. For example, as a sales representative, you can use a dashboard to see graphs of products sold in your territory. Data Loader is a component that enables you to load data from files, such as Microsoft Excel spreadsheets, into destination tables in Oracle Database Cloud Service. The data that you upload can be used in a data model that can then be exposed as a subject area in Oracle BI Cloud Service. Data Modeler is a component that enables you to model data in Oracle BI Cloud Service. The data model that you create is exposed as a subject area that you can use when building analyses and dashboards. Use Data Modeler to add source tables and views to the model, specify joins, create hierarchies to support drilling, and perform other data modeling tasks. In the data model, derived attributes are columns in dimension tables that are based on expressions. For example, a derived attribute called Full Address might combine information from the columns Street Address, City, State, and Postal Code. In the data model, dimension tables contain values that represent the business entities that you measure. A dimension table contains the columns that represent your dimensional attributes, such as places, offices, people, and products. For example, you might want to report dimensions such as Sales by Product Category for the Current Month. In the data model, fact tables contain the numeric data that you use to measure business performance. A fact table contains numeric values such as revenue, number of units sold, and number of people hired. Filters are the criteria that you apply to attribute and measure columns to limit the results that are displayed when an analysis is run. You can create inline or named filters. When you save a filter inside an individual content object, that object is saved "inline." You can save A-2 Using Oracle Business Intelligence Cloud Service

Term group hierarchy identity domain join level measure Oracle BI Cloud Service Data Loader Oracle BI Cloud Service Data Sync Presentation Services project prompt Definition filters, groups, and calculated items inline. In addition to saving these objects inline, you can create individual named filters in the catalog that you can reuse in any analysis, dashboard, or dashboard page. For example, as a sales consultant, you can filter the results that are shown in an existing analysis to see revenue for only those brands for which you are responsible. A group (also known as a "saved selection" in certain products) enables you to define the members of a column, as a list of members or a set of selection steps that generate a list of members. For example, as a sales analyst, you can review how much revenue was generated for mobile devices and compare that number to other product types. You can create a group called Mobile Devices for the Product column that includes Flip Phones and Smart Phones. In the data model, hierarchies show relationships among groups of attribute columns in a dimension table. For example, days comprise months and months comprise quarters. Hierarchies enable drilling in analyses. The identity domain is the user information that provides authentication into Oracle BI Cloud Service. The identity domain also defines roles that groups of users can be members of. In the data model, joins indicate relationships between one fact table and one dimension table. Every fact table must be joined to at least one dimension table, and the reverse. In the data model, levels are components of hierarchies that either roll up or are rolled up from other levels. Hierarchies typically begin with a total level, then have child levels, working down to the lowest level. All levels, except the total level, must have at least one column. A measure is a column in a table that has an aggregation rule defined or is based on an expression that uses other measure columns. For example, you might want to measure business performance by Revenue and Units. Measures are calculated from data sources at query time. Contrast a measure with an attribute. This is a wizard-based too that enables you to upload data from onpremises sources to Oracle Database Cloud Service. Your data can be uploaded from text files (TXT and CSV) or Microsoft Excel spreadsheets (XLS and XLSX). This is a wizard-driven utility that enables you to upload on-premises relational sources or CSV files to Oracle Database Cloud Service. This tool synchronizes on-premises data with Oracle Database Cloud Service using the REST API. You can use this tool for both initial and incremental data loads, as well as run, monitor, and schedule data loads. Oracle does not officially support this tool, nor guarantee that it will be supported in future releases. The collective term for features in Oracle BI Cloud Service that enable you to present business intelligence data. These features include analyses, dashboards and a catalog to present the content. The container for Visual Analyzer data elements and visualizations. Prompts are a type of filter that enable you to build and specify data values, or to choose specific data values to provide result sets for analyses included on a dashboard or dashboard page. A prompt expands or refines the existing dashboard and analysis filters. For Terminology A-3

Term REST API selection step Service Console snapshot source view SQL Developer SQL Workshop table time dimension Definition example, you can use a prompt for Year to specify the year for which you want to see data in an analysis Oracle BI Cloud Service REST API allows you to programmatically create, manage, and load schemas, tables, and data into Oracle BI Cloud Service. You use the Oracle BI Cloud Service REST API if you want to define or customize your own API. As you specify which data members to include in an analysis, you create selections of data from the data source. Each selection specifies the criteria for a set of members for a particular column, such as Product or Geography, and consists of one or more steps. A step is where you specify an instruction that affects the selection, such as add Product members whose values contain the text "ABC." The order in which steps are performed affects the selection of data. Each of your steps acts incrementally on the results from previous steps, rather than acting on all the members for that column. For example, you can create a step to specify criteria for a set of members in a Sales Office column, which contains the members "Boston", "New York", and "San Francisco." Administrators can manage user permissions, back up and restore content, and change the database connection from the Service Console. Snapshots enable you to capture and later restore Oracle BI Cloud Service content at a point in time. A snapshot can include information about the data model, the catalog, and application roles. In the data model, source views are saved queries of the data in the database. You can define source views that combine columns from multiple source tables into a single virtual table. You can create source views to consolidate snowflake sources that have dimension attributes in multiple tables. Oracle SQL Developer is an integrated, transparent, and seamless bulkdata loading facility with full object browsing capabilities. This Javabased tool runs on a client machine and accesses your Oracle BI Cloud Service through a set of RESTful Web Service calls that allow you to access and load data and data structures into Oracle BI Cloud Service. You can develop and deploy web applications for desktops and mobile devices using SQL Workshop, which is part of Oracle Application Express (Oracle APEX). You use a web browser to develop SQL or PL/SQL scripts that can then be used to execute queries against objects in Oracle Database Cloud Service, create and maintain indices, drop unneeded objects, and so on. Similar to database tables, Oracle BI Cloud Service has the concept of a table and uses it in various contexts. When you model data, you create a dimension table or a fact table that includes source columns from one or more source tables in Oracle Database Cloud Service. When you build an analysis, you can create a user-defined table view to display the data. In the data model, time dimensions enable time-series functions. These functions enable comparisons with previous time periods, enabling you to analyze data that spans multiple time periods. A time dimension is a group of the following related model objects: A time source table in the database that is populated with time data A time dimension table in the data model that is based on the time source table A-4 Using Oracle Business Intelligence Cloud Service

Term variable view Visual Analyzer Definition A time hierarchy that defines the relationships between different time periods In the data model, variables dynamically calculate and store values so that you can use those values in expressions. You can use variables in column expressions or in data filters. A view is a visualization that helps communicate an outcome. A view enables you to look at results of analyses in meaningful, intuitive ways. You can add a variety of views to the results, such as graphs and pivot tables, that enable drilling down to more detailed information, explanatory text, a list of filters that were used to limit the results, and more. For example, you can analyze trends for the Sales Forecast analysis by creating a trellis view. A web-based tool that enables you to explore Oracle analytics data visually and on an individual basis. Terminology A-5

B Frequently Asked Questions for Oracle Business Intelligence Cloud Service This reference provides answers to frequently asked questions for Oracle BI Cloud Service. References: Top FAQs for Analyses and Dashboards How does Oracle Business Intelligence Cloud Service differ from Oracle Business Intelligence on-premises? When I want to save an object, where does the default location come from? Can I enable other users to access my custom analyses and dashboards? Can I make analyses and dashboards interact with prompts and other analyses? I have interacted with a dashboard drilling and applying filters. How do I save the state of my dashboard and share the dashboard with others? Can I migrate analyses between different Oracle BI Cloud Service environments? Top FAQs for Data Loading Can I verify that Data Loader has loaded the data as expected? Can I modify the data after it is uploaded? What methods are available to load data to Oracle Database Cloud Service? Can I use the REST API to load data to Oracle Database Cloud Service? Can I drop tables that are no longer needed? Can I load non-utf8 data? How do I upload data that includes date formats other than MMDDYYYY? Top FAQs for Data Modeling Can I use the same data for different analyses? After adding new columns to my source table, can I include the new columns in my data model? In what situations should I create model objects based on source views? Frequently Asked Questions for Oracle Business Intelligence Cloud Service B-1

Top FAQs for Analyses and Dashboards Can I include columns from a different source table in my existing dimension table when it is based on a source view? Can I include columns from a different source table or view in my existing dimension table when it is based directly on a source table? Can I create a source view that is based on another source view? Can I migrate my data model from one Oracle BI Cloud Service environment to another? Top FAQs for Managing Oracle BI Cloud Service How do I upgrade my Oracle BI Cloud Service? Can I track how many users sign in to Oracle BI Cloud Service? Can I see how many users are currently signed in to Oracle BI Cloud Service? Can I see the SQL generated by an analysis and analyze the log? What happens to all my content if I terminate my subscription to Oracle BI Cloud Service? Top FAQs for Analyses and Dashboards The top FAQs for analyses and dashboards are identified in this topic. How does Oracle Business Intelligence Cloud Service differ from Oracle Business Intelligence on-premises? If you have used Oracle BI Enterprise Edition 11g Release 1 (11.1.1.7), then Oracle BI Cloud Service will be familiar to you. In some areas, Oracle BI Cloud Service provides nearly identical features and functionality to Oracle BI EE. These similarities enable you to become more productive more quickly using Oracle BI Cloud Service. When I want to save an object, where does the default location come from? You can save any object in any location. However, the Save In field in the Save dialog sometimes recommends the best location based on the object type that you are saving. For example, you should save filters, groups, and calculated items within a subject area folder so that these items are available when you build an analysis for the same subject area. If a subject area folder does not exist in your /My Folders or within / Shared Folders, then a subject area folder is created automatically. The Save In field defaults a save path to /My Folders/Subject Area Contents/<subject area>; however, the dialog's Folders area displays all instances of the subject area folder in the catalog. You can save other objects such as analyses and prompts in any folder. Bear in mind the distinctions between shared and personal folders, when deciding whether to share the object that you are saving with others. Can I enable other users to access my custom analyses and dashboards? Yes. You can enable other users to access your analyses and dashboards. You can give other users permissions to access the objects, as described in Assigning Permissions to Objects. You can also move the objects to the Company Shared folder. B-2 Using Oracle Business Intelligence Cloud Service

Top FAQs for Data Loading Can I make analyses and dashboards interact with prompts and other analyses? Yes, analyses and dashboards interact with prompts as described in Advanced Techniques: How Dashboard Prompts and Analysis Prompts Interact. You can link views such that one view drives changes in one or more other views. For information, see Linking Views in Master-Detail Relationships. I have interacted with a dashboard drilling and applying filters. How do I save the state of my dashboard and share the dashboard with others? You can save and get back the settings that you make on a dashboard, as described in Recalling Personalized Settings. You can share dashboard pages with other users by sharing links to those pages. For information, see Linking to Dashboard Pages. Can I migrate analyses between different Oracle BI Cloud Service environments? Yes. You can migrate analyses between service environments by copying and pasting the XML code for the analyses using the Advanced tab of the Analysis editor. For information, see Advanced Techniques: Examining the Logical SQL Statements for Analyses. Top FAQs for Data Loading The top FAQs for data loading are identified in this topic. Can I verify that Data Loader has loaded the data as expected? Yes. You can view load history on the Home page in Data Loader. In addition, Oracle Database Cloud Service (Database Schema) provides utilities, including Oracle Application Express SQL Workshop, to validate data in tables. Can I modify the data after it is uploaded? Yes. You can use the Oracle Application Express SQL Workshop utility to perform general database tasks for data loaded into Oracle Database Cloud Service. What methods are available to load data to Oracle Database Cloud Service? You can use various methods for loading data into Oracle Database Cloud Service. These methods depend on the type of source data that you want to load (for example, relational tables or CSV files). You can: Load your data from files directly by using the web-based Data Loader. See Loading Data from Files for more information. Load data from relational tables. See Loading Data from Relational Tables for more information. Load data from relational tables (for example, an Oracle database). See Loading Relational Tables Using SQL Developer. Use programmatic methods, such as PL/SQL scripts or the REST API to automate data loading. See Automating Loading Data Using Programmatic Methods for additional information. See Uploading Your Data to the Cloud. Frequently Asked Questions for Oracle Business Intelligence Cloud Service B-3

Top FAQs for Data Modeling Can I use the REST API to load data to Oracle Database Cloud Service? Yes. You can define or customize your own API and programmatically load onpremises data to Oracle Database Cloud Service. The REST API is optimized for loading large volumes of data (thousands to millions) from one or more sources. See Automating Loading Data Using Programmatic Methods for additional information. Can I drop tables that are no longer needed? Yes. You can use Oracle Application Express SQL Workshop to drop tables in Oracle Database Cloud Service. Can I load non-utf8 data? No. Currently, Data Loader supports UTF8 characters in data files. How do I upload data that includes date formats other than MMDDYYYY? Data Loader loads data in MMDDYYYY date format. To upload data with date formats other than MMDDYYYY, use Data Workshop utilities in Oracle Application Express SQL Workshop. Top FAQs for Data Modeling The top FAQs for data modeling are identified in this topic. Can I use the same data for different analyses? Yes. You can create source views that expose the same source columns in different contexts. You use views to include the same source objects in multiple dimensions. For example, to use time data for both the Order Date and Ship Date dimensions, create two views based on the time source table, time_order_date_v and time_ship_date_v. The views can then be used as sources for the Order Date and Ship Date dimensions. After adding new columns to my source table, can I include the new columns in my data model? Yes. You can include newly added source columns. To include the new columns, select Synchronize with Database from the Actions menu for the appropriate fact table or dimension table in the Data Model. Then, in the messages list, select the message item describing the new columns and select Sync-up selected from the Message Actions menu. In what situations should I create model objects based on source views? Always create a source view when you think that you might want to perform subsequent changes, such as extending model objects, creating filters, and adding calculations. Creating a model based on source views provides greater flexibility than using source tables directly. Can I include columns from a different source table or view in my existing dimension table when it is based directly on a source table? Yes. It's easy to add columns from another source table or view to an existing dimension table. To do this, drag and drop the table or view on to your existing dimension table. See Adding Columns from Another Source to a Dimension Table. B-4 Using Oracle Business Intelligence Cloud Service

Top FAQs for Managing Oracle BI Cloud Service Can I include columns from a different source table in my existing dimension table when it is based on a source view? Yes. There are two ways you can do this. You can drag and drop the table on to the dimension table to include the columns. Alternatively, edit the view to include the new source columns, and synchronize your dimension table with your changes to the database. Synchronization identifies new columns in the view and adds them to your dimension table. Can I create a source view that is based on another source view? Yes. To do this, drag and drop the source view to the Columns area of the Overview tab when creating the view, or select a source view from the Add Columns dialog as your source. For example, assume that you have both time and time_fiscal source tables. You created a view called time_v that combines time and time_fiscal. You want to create multiple dimensions that are based on time data, such as Order Day and Ship Day. You first create the Order Day dimension based on time_v, and then you create a separate view on top of time_v to create Ship Day. (Note that another option is to create a parallel view called ship_day_v that also combines time and time_fiscal.) Can I migrate my data model from one Oracle BI Cloud Service environment to another? Yes. To do this, take a snapshot of your Oracle BI Cloud Service and migrate it to the new environment. See Backing Up and Restoring for more information. Top FAQs for Managing Oracle BI Cloud Service The top FAQs for managing Oracle BI Cloud Service are identified in this topic. How do I upgrade my Oracle BI Cloud Service? Everyone who subscribes to Oracle BI Cloud Service receives automatic upgrades as soon as new versions become available. You don't need to request an upgrade or take any actions yourself. To find out about recent new features and enhancements, see What's New? Can I track how many users sign in to Oracle BI Cloud Service? Yes. Administrators for Oracle BI Cloud Service can monitor how many users sign in to the service. Click Business Intelligence or Database from the Platform Services tab in the Oracle Cloud My Services page. See Viewing Service Details in My Services in Getting Started with Oracle Cloud for more information. Can I see how many users are currently signed in to Oracle BI Cloud Service? Yes. Display the Home page for Oracle BI Cloud Service and select Manage Sessions from the Administration menu. See Accessing Oracle BI Cloud Service and Monitoring Users Who Are Signed In. Can I see the SQL generated by an analysis and analyze the log? Yes. Display the Home page for Oracle BI Cloud Service and select Manage Sessions from the Administration menu. See Accessing Oracle BI Cloud Service and Analyzing SQL Queries and Logs for more information. Frequently Asked Questions for Oracle Business Intelligence Cloud Service B-5

Top FAQs for Managing Oracle BI Cloud Service What happens to all my content if I terminate my subscription to Oracle BI Cloud Service? When you terminate your subscription to Oracle BI Cloud Service, Oracle takes a snapshot of the latest data model, catalog content, and application roles. The snapshot is sent to you in a password-protected Oracle Business Intelligence archive (.bar) file. If you subscribe to Oracle BI Cloud Service in the future, you can import content from this archive file. The password that you need to upload the archive file to another service is IdentityDomainName_ServiceName. See Uploading Snapshots and Restoring from a Snapshot. B-6 Using Oracle Business Intelligence Cloud Service

C Troubleshooting Oracle Business Intelligence Cloud Service This topic describes common problems that you might encounter when using Oracle Business Intelligence Cloud Service and explains how to solve them. Topics: Troubleshooting General Issues I can t sign in to Oracle BI Cloud Service I'm having trouble resetting my password I can t access certain options from the Home page of Oracle BI Cloud Service Troubleshooting Issues with Analyses and Dashboards I can t see data in an analysis I can t access a particular analysis or dashboard I can t find an analysis or dashboard The analysis is running very slowly The analysis returned data that I did not expect I don t understand why my analysis shows a view display error Troubleshooting Data Loading Issues I m trying to load data but Data Loader stopped responding Data in my file is not being read properly Data was uploaded with many errors Formulas in my Excel spreadsheet are loading instead of the values Troubleshooting Data Modeling Issues I can t see any tables or views in Data Modeler I can t see the left pane in Data Modeler I can t edit any objects in Data Modeler I can t lock the data model Troubleshooting Oracle Business Intelligence Cloud Service C-1

Troubleshooting General Issues I can t publish the data model Why must I use the SQL Query tab to edit a join or filter for a view? I see the message: Cluster error-no active server node found Troubleshooting Administration Issues I can t find the Administration menu option I m looking for I can t access tabs in the Service Console Troubleshooting General Issues This topic describes common problems that you might encounter when working with Oracle BI Cloud Service and explains how to solve them. I can t sign in to Oracle BI Cloud Service You re likely trying to sign in using the incorrect credentials. You must sign in to Oracle BI Cloud Service using the Oracle Cloud Identity Domain credentials that were mailed to you from Oracle or provided by your administrator. You can t sign in to Oracle BI Cloud Service using your account credentials for Oracle.com. I'm having trouble resetting my password When you sign up to use Oracle BI Cloud Service, you get an e-mail with a temporary password. Be careful if you copy and paste this password. If you accidentally include a blank space at the start or end of it when copying, then the password won't be recognized when you paste it in. Make sure that you paste only the password without any blank spaces. I can t access certain options from the Home page of Oracle BI Cloud Service Check with your administrator to ensure that you have the correct permissions to use access the options that need. Troubleshooting Issues with Analyses and Dashboards This topic describes common problems that you might encounter when using analyses and dashboards, and explains how to solve them. I can t see data in an analysis You open an analysis but do not see any data in it. There might be some temporary issue with the database. Contact your administrator for assistance. I can t access a particular analysis or dashboard You attempt to display an analysis or dashboard and find that you do not have access. Typically you cannot access an analysis or dashboard if you lack the appropriate permissions or application role for accessing it. Contact the owner of the analysis or dashboard or your administrator for assistance in obtaining the proper permissions or application role. See Assigning Permissions to Objects and Assigning Application Roles to Users. C-2 Using Oracle Business Intelligence Cloud Service

Troubleshooting Data Loading Issues I can t find an analysis or dashboard Try searching the catalog. You can search for analyses and dashboards by name (full or partial) and by folder location. The search is not case-sensitive. Searches of the catalog return only those objects that you have permission to see. For more tips, see Finding and Exploring Your Content. Contact your administrator if you still can t find an analysis or dashboard and you suspect it was deleted by mistake. Your administrator can restore earlier versions of the catalog from recent snapshots, if required. The analysis is running very slowly You attempt to run an analysis and find that it takes a long time. Various underlying circumstances can cause an analysis to run slowly. Contact your administrator and ask that he review log files associated with the analysis, as described in Managing Session Information in Oracle BI Cloud Service. After reviewing the log files with the administrator, make the appropriate adjustments in the analysis. The analysis returned data that I did not expect Various underlying circumstances can cause an analysis to return unexpected results. In the Subject Areas pane of the Criteria tab, click Refresh to ensure you re seeing the most recent information. Alternatively: Ask a data modeler or an administrator to reload underlying data to ensure that any recent changes to the data model are reflected in the analysis. Data modelers and administrators can access the Reload Server Metadata option when they click the Refresh icon in the Subject Areas pane of the Criteria tab. Ask your administrator to review log files for the analysis, as described in Analyzing SQL Queries and Logs. After reviewing the log files with the administrator, make appropriate adjustments in the analysis. I don t understand why my analysis shows a view display error When you display an analysis, you might see a message such as the following: "View Display Error. Exceed configured maximum number of allowed input records." This message indicates that you've selected more data than can be displayed in a view of that type. Add one or more filters to the analysis to reduce the amount of data. For example, add a filter that specifies a date range of only a few years. Troubleshooting Data Loading Issues This topic describes common problems that you might encounter when loading data and explains how to solve them. I m trying to load data but Data Loader stopped responding You might be loading a file that is beyond the expected limits of Data Loader. For more information, see Uploading Your Data to the Cloud. Use Oracle SQL Developer rather than Data Loader for loading very large amounts of data. As a guideline, use Oracle SQL Developer for input files greater than 500,000 rows. For more information, see Loading Relational Tables Using SQL Developer Troubleshooting Oracle Business Intelligence Cloud Service C-3

Troubleshooting Data Modeling Issues Data in my file is not being read properly Verify that the data records in the file that you are loading are separated by a delimiter that Data Loader supports such as comma, tab, or pipe. If the file includes the proper delimiter, then verify that you specified the appropriate delimiter on the Select Data page of Data Loader. Data was uploaded with many errors Go to the Home page, click Data Loader, and locate the column labeled Not Loaded Records for your particular upload to see why some records failed to load properly. After correcting the errors, click Reload records to upload the records. Formulas in my Excel spreadsheet are loading instead of the values Remove the formula or replace the formula with data values from your spreadsheet, and then reload the records that were in error. Troubleshooting Data Modeling Issues This topic describes common problems that you might encounter when modeling data and explains how to solve them. I can t see any tables or views in Data Modeler If you start Data Modeler and see no tables or views, then one of the following has occurred: No tables have been created in the schema. Use Data Loader or SQL Developer to create tables. You have displayed Data Modeler before creating a table in Data Loader, and Data Modeler does not show the latest schema objects. To see the latest objects, refresh the Database pane in Data Modeler. I can t see the left pane in Data Modeler The left pane in Data Modeler is collapsed. To display the left pane, click the Restore Pane icon displayed on the left of the page. I can t edit any objects in Data Modeler You must always lock the data model before making any changes. Click Lock to Edit to lock the data model. I can t lock the data model Check whether someone else locked the data model. If you re an administrator, then you can override the lock. Otherwise, wait until the lock is released. For more information, See Overriding Locks in Locking the Data Model.. I can t publish the data model Check whether you have Data Modeler open in multiple browser tabs or multiple browser windows. If you do, close any additional browser tabs and windows running Data Modeler, and try publishing the model again. If you still get a publishing error, then restart the browser. C-4 Using Oracle Business Intelligence Cloud Service

Troubleshooting Administration Issues Why must I use the SQL Query tab to edit a join or filter for a view? The message Please use SQL Query tab to edit Joins/Filters is displayed when you click the Joins tab or the Filters tab in the view editor for one of the following reasons: Oracle BI Cloud Service can t parse the SQL query for the database view If you use only the Overview, Joins, and Filters tabs to edit a database view, then Oracle BI Cloud Service constructs a simple SQL query for you. If you decide to edit the SQL manually through the SQL Query tab, then simple updates are reflected back in the Overview, Join, and Filters tabs so you can use these tabs to further edit the view later on. If, however, you have used the SQL Query tab to make more advanced code changes, then you can t use the Overview, Joins or Filters tabs to further edit the view because Oracle BI Cloud Service can t verify your updates. For example, if you include: SQL aggregation functions, GROUP BY clause, HAVING clause ORDER BY clause OR keyword in WHERE clause UNION clause Oracle BI Cloud Service can t access the database view If the problem persists, report the issue to your administrator. Your administrator can investigate connection issues relating to your database service. I see the message: Cluster error-no active server node found The instance of Oracle BI Cloud Service might be down or the database might be locked. If the problem persists, then report the issue to an administrator. Troubleshooting Administration Issues This topic describes common problems that you might encounter when performing administration tasks and explains how to solve them. I can t find the Administration menu option I m looking for If you can t see the Administration menu or the Administration menu option that you re looking for, you probably don t have the required permissions. Ask an administrator to verify your permissions. See Assigning Application Roles to Users. You need the following application roles to access Administration menus options: Administration Menu Option User and Role Admin Data Loader Data Modeler Manage Sessions Issue SQL Application Role Required BI Service Administrator BI Data Model Author BI Data Model Author BI Service Administrator BI Service Administrator Troubleshooting Oracle Business Intelligence Cloud Service C-5

Troubleshooting Administration Issues I can t access tabs in the Service Console If you see an "unauthorized message" when you click a tab in the Service Console, you probably don t have the BI Service Administrator application role. You must have the BI Service Administrator application role to access tabs on this page (such as Application Role Management and Snapshot). Ask an administrator to verify your permissions. See Assigning Application Roles to Users. C-6 Using Oracle Business Intelligence Cloud Service

D Expression Editor Reference This topic describes the Expression Elements that you can use in the Expression Editor in Data Modeler. Topics: Data Model Objects SQL Operators Conditional Expressions Functions Constants Types Variables Data Model Objects You can use data model objects in expressions, like time levels, dimension columns, and fact columns. To reference a data model object, use the syntax: "Fact/Dimension Table Name"."Column Name" For example: "Order Metrics"."Booked Amount"-"Order Metrics"."Fulfilled Amount" The Expression Elements section includes only items that are relevant for your task, so not all fact tables and dimension tables might be listed. Similarly, time hierarchies are included only if the Time fact table is joined to the current table. SQL Operators SQL operators are used to specify comparisons between expressions. You can use various types of SQL operators. Operator BETWEEN IN IS NULL Description Determines if a value is between two non-inclusive bounds. For example: "COSTS"."UNIT_COST" BETWEEN 100.0 AND 5000.0 BETWEEN can be preceded with NOT to negate the condition. Determines if a value is present in a set of values. For example: "COSTS"."UNIT_COST" IN(200, 600, 'A') Determines if a value is null. For example: Expression Editor Reference D-1

Conditional Expressions Operator LIKE Description "PRODUCTS"."PROD_NAME" IS NULL Determines if a value matches all or part of a string. Often used with wildcard characters to indicate any character string match of zero or more characters (%) or any single character match (_). For example: "PRODUCTS"."PROD_NAME" LIKE 'prod%' Conditional Expressions You use conditional expressions to create expressions that convert values. The conditional expressions described in this section are building blocks for creating expressions that convert a value from one form to another. Note: In CASE statements, AND has precedence over OR Strings must be in single quotes Expression Example Description CASE (If) CASE (Switch) CASE WHEN score-par < 0 THEN 'Under Par' WHEN score-par = 0 THEN 'Par' WHEN score-par = 1 THEN 'Bogey' WHEN score-par = 2 THEN 'Double Bogey' ELSE 'Triple Bogey or Worse' END CASE Score-par WHEN -5 THEN 'Birdie on Par 6' WHEN -4 THEN 'Must be Tiger' WHEN -3 THEN 'Three under par' WHEN -2 THEN 'Two under par' WHEN -1 THEN 'Birdie' WHEN 0 THEN 'Par' WHEN 1 THEN 'Bogey' WHEN 2 THEN 'Double Bogey' ELSE 'Triple Bogey or Worse' END Evaluates each WHEN condition and if satisfied, assigns the value in the corresponding THEN expression. If none of the WHEN conditions are satisfied, it assigns the default value specified in the ELSE expression. If no ELSE expression is specified, the system automatically adds an ELSE NULL. Also referred to as CASE (Lookup). The value of the first expression is examined, then the WHEN expressions. If the first expression matches any WHEN expression, it assigns the value in the corresponding THEN expression. If none of the WHEN expressions match, it assigns the default value specified in the ELSE expression. If no ELSE expression is specified, the system automatically adds an ELSE NULL. If the first expression matches an expression in multiple WHEN clauses, only the expression following the first match is assigned. Functions There are various types of functions that you can use in expressions. Topics: Aggregate Functions Calendar Functions Conversion Functions D-2 Using Oracle Business Intelligence Cloud Service

Functions Aggregate Functions Display Functions Evaluate Functions Mathematical Functions String Functions System Functions Time Series Functions Aggregate functions perform operations on multiple values to create summary results. Function Example Description Avg Avg(Sales) Calculates the average (mean) of a numeric set of values. Count Count(Products) Determines the number of items with a non-null value. First First(Sales) Selects the first non-null returned value of the expression argument. The First function operates at the most detailed level specified in your explicitly defined dimension. Last Last(Sales) Selects the last non-null returned value of the expression. Max Max(Revenue) Calculates the maximum value (highest numeric value) of the rows satisfying the numeric expression argument. Median Median(Sales) Calculates the median (middle) value of the rows satisfying the numeric expression argument. When there are an even number of rows, the median is the mean of the two middle rows. This function always returns a double. Min Min(Revenue) Calculates the minimum value (lowest numeric value) of the rows satisfying the numeric expression argument. StdDev StdDev_Pop StdDev(Sales) StdDev(DISTINCT Sales) StdDev_Pop(Sales) StdDev_Pop(DISTINCT Sales) Returns the standard deviation for a set of values. The return type is always a double. Returns the standard deviation for a set of values using the computational formula for population variance and standard deviation. Sum Sum(Revenue) Calculates the sum obtained by adding up all values satisfying the numeric expression argument. Calendar Functions Calendar functions manipulate data of the data types DATE and DATETIME based on a calendar year. Function Example Description Current_Date Current_Date Returns the current date. Current_Time Current_Time(3) Returns the current time to the specified number of digits of precision, for example: HH:MM:SS.SSS If no argument is specified, the function returns the default precision. Expression Editor Reference D-3

Functions Function Example Description Current_TimeStam p Current_TimeStamp(3) Returns the current date/timestamp to the specified number of digits of precision. DayName DayName(Order_Date) Returns the name of the day of the week for a specified date expression. DayOfMonth DayOfMonth(Order_Date) Returns the number corresponding to the day of the month for a specified date expression. DayOfWeek DayOfWeek(Order_Date) Returns a number between 1 and 7 corresponding to the day of the week for a specified date expression. For example, 1 always corresponds to Sunday, 2 corresponds to Monday, and so on through to Saturday which returns 7. DayOfYear DayOfYear(Order_Date) Returns the number (between 1 and 366) corresponding to the day of the year for a specified date expression. Day_Of_Quarter Day_Of_Quarter(Order_Date) Returns a number (between 1 and 92) corresponding to the day of the quarter for the specified date expression. Hour Hour(Order_Time) Returns a number (between 0 and 23) corresponding to the hour for a specified time expression. For example, 0 corresponds to 12 a.m. and 23 corresponds to 11 p.m. Minute Minute(Order_Time) Returns a number (between 0 and 59) corresponding to the minute for a specified time expression. Month Month(Order_Time) Returns the number (between 1 and 12) corresponding to the month for a specified date expression. MonthName MonthName(Order_Time) Returns the name of the month for a specified date expression. Month_Of_Quarter Month_Of_Quarter(Order_Dat e) Returns the number (between 1 and 3) corresponding to the month in the quarter for a specified date expression. Now Now() Returns the current timestamp. The Now function is equivalent to the Current_Timestamp function. Quater_Of_Year Quarter_Of_Year(Order_Date ) Returns the number (between 1 and 4) corresponding to the quarter of the year for a specified date expression. Second Second(Order_Time) Returns the number (between 0 and 59) corresponding to the seconds for a specified time expression. TimeStampAdd TimeStampDiff TimeStampAdd(SQL_TSI_MONTH, 12,Time."Order Date") TimeStampDiff(SQL_TSI_MONT H, Time."Order Date",CURRENT_DATE) Adds a specified number of intervals to a timestamp, and returns a single timestamp. Interval options are: SQL_TSI_SECOND, SQL_TSI_MINUTE, SQL_TSI_HOUR, SQL_TSI_DAY, SQL_TSI_WEEK, SQL_TSI_MONTH, SQL_TSI_QUARTER, SQL_TSI_YEAR Returns the total number of specified intervals between two timestamps. Use the same intervals as TimeStampAdd. D-4 Using Oracle Business Intelligence Cloud Service

Functions Function Example Description Week_Of_Quarter Week_Of_Quarter(Order_Date ) Returns a number (between 1 and 13) corresponding to the week of the quarter for the specified date expression. Week_Of_Year Week_Of_Year(Order_Date) Returns a number (between 1 and 53) corresponding to the week of the year for the specified date expression. Year Year(Order_Date) Returns the year for the specified date expression. Conversion Functions Conversion functions convert a value from one form to another. Function Example Description Cast Cast(hiredate AS CHAR(40)) FROM employee Changes the data type of an expression or a null literal to another data type. For example, you can cast a customer_name (a data type of Char or Varchar) or birthdate (a datetime literal). Use Cast to change to a Date data type. Do not use ToDate. IfNull IfNull(Sales, 0) Tests if an expression evaluates to a null value, and if it does, assigns the specified value to the expression. IndexCol NullIf To_DateTime SELECT IndexCol(VALUEOF (NQ_SESSION.GEOGRAPHY_LE VEL), Country, State, City), Revenue FROM Sales SELECT e.last_name, NULLIF(e.job_id, j.job_id) "Old Job ID" FROM employees e, job_history j WHERE e.employee_id = j.employee_id ORDER BY last_name, "Old Job ID"; SELECT To_DateTime ('2009-03-0301:01:00', 'yyyy-mm-dd hh:mi:ss') FROM sales Uses external information to return the appropriate column for the signed-in user to see. Compares two expressions. If they are equal, then the function returns null. If they are not equal, then the function returns the first expression. You cannot specify the literal NULL for the first expression. Converts string literals of datetime format to a DateTime data type. Display Functions Display functions operate on the result set of a query. Function Example Description BottomN BottomN(Sales, 10) Returns the n lowest values of expression, ranked from lowest to highest. Filter Filter(Sales USING Product = 'widgit') Computes the expression using the given preaggregate filter. Mavg Mavg(Sales, 10) Calculates a moving average (mean) for the last n rows of data in the result set, inclusive of the current row. Expression Editor Reference D-5

Functions Function Example Description Msum SELECT Month, Revenue, Msum(Revenue, 3) as 3_MO_SUM FROM Sales Calculates a moving sum for the last n rows of data, inclusive of the current row. The sum for the first row is equal to the numeric expression for the first row. The sum for the second row is calculated by taking the sum of the first two rows of data, and so on. When the nth row is reached, the sum is calculated based on the last n rows of data. NTile Ntile(Sales, 100) Determines the rank of a value in terms of a user-specified range. It returns integers to represent any range of ranks. The example shows a range from 1 to 100, with the lowest sale = 1 and the highest sale = 100. Percentile Percentile(Sales) Calculates a percent rank for each value satisfying the numeric expression argument. The percentile rank ranges are from 0 (1st percentile) to 1 (100th percentile), inclusive. Rank Rank(Sales) Calculates the rank for each value satisfying the numeric expression argument. The highest number is assigned a rank of 1, and each successive rank is assigned the next consecutive integer (2, 3, 4,...). If certain values are equal, they are assigned the same rank (for example, 1, 1, 1, 4, 5, 5, 7...). Rcount Rmax Rmin Rsum SELECT month, profit, Rcount(profit) FROM sales WHERE profit > 200 SELECT month, profit, Rmax(profit) FROM sales SELECT month, profit, Rmin(profit) FROM sales SELECT month, revenue, Rsum(revenue) as RUNNING_SUM FROM sales Takes a set of records as input and counts the number of records encountered so far. Takes a set of records as input and shows the maximum value based on records encountered so far. The specified data type must be one that can be ordered. Takes a set of records as input and shows the minimum value based on records encountered so far. The specified data type must be one that can be ordered. Calculates a running sum based on records encountered so far. The sum for the first row is equal to the numeric expression for the first row. The sum for the second row is calculated by taking the sum of the first two rows of data, and so on. TopN TopN(Sales, 10) Returns the n highest values of expression, ranked from highest to lowest. Evaluate Functions Evaluate functions are database functions that can be used to pass through expressions to get advanced calculations. Embedded database functions can require one or more columns. These columns are referenced by %1... %N within the function. The actual columns must be listed after the function. Function Example Description Evaluate SELECT EVALUATE('instr(%1, %2)', address, 'Foster City') FROM employees Passes the specified database function with optional referenced columns as parameters to the database for evaluation. D-6 Using Oracle Business Intelligence Cloud Service

Functions Function Example Description Evaluate_Aggr EVALUATE_AGGR('REGR_SLOP E(%1, %2)', sales.quantity, market.marketkey) Passes the specified database function with optional referenced columns as parameters to the database for evaluation. This function is intended for aggregate functions with a GROUP BY clause. Mathematical Functions The mathematical functions described in this section perform mathematical operations. Function Example Description Abs Abs(Profit) Calculates the absolute value of a numeric expression. Acos Acos(1) Calculates the arc cosine of a numeric expression. Asin Asin(1) Calculates the arc sine of a numeric expression. Atan Atan(1) Calculates the arc tangent of a numeric expression. Atan2 Atan2(1, 2) Calculates the arc tangent of y/x, where y is the first numeric expression and x is the second numeric expression. Ceiling Ceiling(Profit) Rounds a noninteger numeric expression to the next highest integer. If the numeric expression evaluates to an integer, the CEILING function returns that integer. Cos Cos(1) Calculates the cosine of a numeric expression. Cot Cot(1) Calculates the cotangent of a numeric expression. Degrees Degrees(1) Converts an expression from radians to degrees. Exp Exp(4) Sends the value to the power specified. ExtractBit Int ExtractBit(1, 5) Retrieves a bit at a particular position in an integer. It returns an integer of either 0 or 1 corresponding to the position of the bit. Floor Floor(Profit) Rounds a noninteger numeric expression to the next lowest integer. If the numeric expression evaluates to an integer, the FLOOR function returns that integer. Log Log(1) Calculates the natural logarithm of an expression. Log10 Log10(1) Calculates the base 10 logarithm of an expression. Mod Mod(10, 3) Divides the first numeric expression by the second numeric expression and returns the remainder portion of the quotient. Pi Pi() Returns the constant value of pi. Power Power(Profit, 2) Takes the first numeric expression and raises it to the power specified in the second numeric expression. Radians Radians(30) Converts an expression from degrees to radians. Rand Rand() Returns a pseudo-random number between 0 and 1. RandFromSee d Rand(2) Returns a pseudo-random number based on a seed value. For a given seed value, the same set of random numbers are generated. Round Round(2.166000, 2) Rounds a numeric expression to n digits of precision. Expression Editor Reference D-7

Functions Function Example Description Sign Sign(Profit) This function returns the following: 1 if the numeric expression evaluates to a positive number -1 if the numeric expression evaluates to a negative number 0 if the numeric expression evaluates to zero Sin Sin(1) Calculates the sine of a numeric expression. Sqrt Sqrt(7) Calculates the square root of the numeric expression argument. The numeric expression must evaluate to a nonnegative number. Tan Tan(1) Calculates the tangent of a numeric expression. Truncate Truncate(45.12345, 2) Truncates a decimal number to return a specified number of places from the decimal point. String Functions String functions perform various character manipulations. They operate on character strings. Function Example Description Ascii Ascii('a') Converts a single character string to its corresponding ASCII code, between 0 and 255. If the character expression evaluates to multiple characters, the ASCII code corresponding to the first character in the expression is returned. Bit_Length Bit_Length('abcdef') Returns the length, in bits, of a specified string. Each Unicode character is 2 bytes in length (equal to 16 bits). Char Char(35) Converts a numeric value between 0 and 255 to the character value corresponding to the ASCII code. Char_Length Concat Insert Char_Length(Customer_Nam e) SELECT DISTINCT Concat ('abc', 'def') FROM employee SELECT Insert('123456', 2, 3, 'abcd') FROM table Returns the length, in number of characters, of a specified string. Leading and trailing blanks are not counted in the length of the string. Concatenates two character strings. Inserts a specified character string into a specified location in another character string. Left SELECT Left('123456', 3) FROM table Returns a specified number of characters from the left of a string. Length Length(Customer_Name) Returns the length, in number of characters, of a specified string. The length is returned excluding any trailing blank characters. Locate Locate('d' 'abcdef') Returns the numeric position of a character string in another character string. If the character string is not found in the string being searched, the function returns a value of 0. LocateN Locate('d' 'abcdef', 3) Like Locate, returns the numeric position of a character string in another character string. LocateN includes an D-8 Using Oracle Business Intelligence Cloud Service

Functions Function Example Description integer argument that enables you to specify a starting position to begin the search. Lower Lower(Customer_Name) Converts a character string to lowercase. Octet_Length Octet_Length('abcdef') Returns the number of bytes of a specified string. Position Position('d', 'abcdef') Returns the numeric position of strexpr1 in a character expression. If strexpr1 is not found, the function returns 0. Repeat Repeat('abc', 4) Repeats a specified expression n times. Replace Right Replace('abcd1234', '123', 'zz') SELECT Right('123456', 3) FROM table Replaces one or more characters from a specified character expression with one or more other characters. Returns a specified number of characters from the right of a string. Space Space(2) Inserts blank spaces. Substring SubstringN TrimBoth TrimLeading TrimTrailing Substring('abcdef' FROM 2) Substring('abcdef' FROM 2 FOR 3) Trim(BOTH '_' FROM '_abcdef_') Trim(LEADING '_' FROM '_abcdef') Trim(TRAILING '_' FROM 'abcdef_') Creates a new string starting from a fixed number of characters into the original string. Like Substring, creates a new string starting from a fixed number of characters into the original string. SubstringN includes an integer argument that enables you to specify the length of the new string, in number of characters. Strips specified leading and trailing characters from a character string. Strips specified leading characters from a character string. Strips specified trailing characters from a character string. Upper Upper(Customer_Name) Converts a character string to uppercase. System Functions Time Series Functions The USER system function returns values relating to the session. It returns the user name you signed in with. Time series functions are aggregate functions that operate on time dimensions. The time dimension members must be at or below the level of the function. Because of this, one or more columns that uniquely identify members at or below the given level must be projected in the query. Function Example Description Ago Periodrolling SELECT Year_ID, Ago(sales, year, 1) SELECT Month_ID, Periodrolling (monthly_sales, -1, 1) Calculates the aggregated value of a measure from the current time to a specified time period in the past. For example, AGO can produce sales for every month of the current quarter and the corresponding quarter-ago sales. Computes the aggregate of a measure over the period starting x units of time and ending y units of time from the current time. For example, PERIODROLLING can compute Expression Editor Reference D-9

Constants Function Example Description sales for a period that starts at a quarter before and ends at a quarter after the current quarter. ToDate SELECT Year_ID, Month_ID, ToDate (sales, year) Aggregates a measure from the beginning of a specified time period to the currently displayed time. For example, this function can calculate Year to Date sales. Constants You can use constants in expressions. Available constants include Date, Time, and Timestamp. See also Current_Date, Current_Time, and Current_TimeStamp. Constant Example Description Date DATE [2014-04-09] Inserts a specific date. Time TIME [12:00:00] Inserts a specific time. TimeStamp TIMESTAMP [2014-04-09 12:00:00] Inserts a specific timestamp. Types Variables You can use data types, such as CHAR, INT, and NUMERIC, in expressions. For example, you use types when creating CAST expressions that change the data type of an expression or a null literal to another data type. Variables are used in expressions. You can use a variable in an expression. See Defining Variables for details. D-10 Using Oracle Business Intelligence Cloud Service

E Accessibility This section provides information on accessibility features for Oracle BI Cloud Service. Topics: About Accessibility Features Changing to Accessibility Mode About Keyboard Shortcuts Navigating with Keystrokes About Accessibility Features The accessibility features in Oracle BI Cloud Service aim to make navigating and using the service easier for persons with disabilities and for the aging population. The accessibility features support the use of standards-based assistive-technology hardware and software (such as Freedom Scientific JAWS). The accessibility features are grouped into these general categories: Features used by third-party assistive-technology products. These features center on providing a user interface that consists of standard HTML elements that can be easily interpreted by third-party assistive technology products. Accessibility mode, as described in Changing to Accessibility Mode. Keyboard shortcuts and tab shortcuts that make it easier to navigate content for users with limited or no ability to use a mouse. Content design capabilities that make it possible for content creators to create content that supports users with accessibility needs. While Oracle BI Cloud Service provides an accessibility mode that offers many features automatically, you as the designer must create content that meets the accessibility requirements of your user community. Changing to Accessibility Mode Accessibility mode makes the user interface more compatible with screen readers. Only features supported for users with disabilities are visible. By default, accessibility mode is not enabled. You can decide whether to enable disability mode during sign in, or after sign in. To enable accessibility mode after signing in: 1. Press Tab multiple times to navigate through the global header, until the focus is on your user name in the Signed In As area. Accessibility E-1

About Keyboard Shortcuts 2. Press Enter, then Tab to highlight the My Account link. 3. Press Enter to display the My Account dialog. 4. Press Tab to select the My Account dialog: Preferences tab. 5. Press Tab to navigate through the fields on the tab until you read the Accessibility Mode options. 6. Use the arrow keys to select the On option. 7. Press Enter to save your changes and close the dialog. 8. Refresh the page to see it in accessibility mode. Note: The Accessibility Mode setting on the My Account: Preferences tab applies to the Presentation Services, Data Loader, Data Modeler, and Service Console. In accessibility mode: The Home page does not contain links for performing most editing functions, such as editing dashboards. Graphs are not displayed. They are converted to one or more annotated tables. Tables and pivot tables are displayed with internal annotations that enable screen readers to describe the contents of cells. Refer to your assistive-technology documentation for table navigation shortcuts. You cannot use a mouse to modify the layout of a table or pivot table. Performance tiles and treemaps are displayed as pivot tables. The upper-left corner of each section on a dashboard page contains a collapse icon. This is true even if the section is marked as not collapsible in the Dashboard builder. The icon is the first element that receives focus when using a keyboard to navigate on a dashboard page. The Page Options button on a dashboard page is not available. If a dashboard page is refreshed, then the location of the focus is not preserved. You must press Tab to navigate through the focusable items. Trellis views displayed on dashboards are converted to pivot table views. Attribute columns of the inner graph are not included. Measure values are aggregated to the new grain of the pivot table views. About Keyboard Shortcuts Oracle BI Cloud Service supports standard keyboard shortcuts that are used in many software applications. In addition, the service offers its own shortcuts. Use general keyboard shortcuts with Oracle BI Cloud Service. E-2 Using Oracle Business Intelligence Cloud Service

Navigating with Keystrokes Keyboard Shortcut Control+Alt+G Control+Alt+D Control+Alt+P Control+Shift+S Control+Shift+U Tab Shift+Tab Down Arrow Up Arrow Enter Esc Result Navigates to the first focusable element in the global header: the Skip to Content link. The link enables you to bypass the options on the global header and move to features on the main part of the Home page. Navigates to the Dashboards popup menu in the global header. You can then press Enter to display a menu from which you can select a dashboard to display. Navigates to the current dashboard page tab, if the tab is displayed. If there is only one page in the dashboard, then the page tab is not displayed. Navigates to the first focusable element in the next section. For a dashboard page, the first element is the collapse icon. Navigates to the first focusable element in the previous section. For a dashboard page, the first element is the collapse icon. Navigates to the next focusable element. Navigates to the previous focusable element. Navigates to the next menu option. Navigates to the previous menu option. Triggers the activity, when the focus in on a link, image, or a button with an associated URL or activity. Closes the menu that has the focus. Use keyboard shortcuts for navigating in dashboards in Oracle BI Cloud Service. Keyboard Shortcut Alt + Up or Down Arrow Control + Up or Down Arrow Result Opens drop-down and combo boxes. Shows the next or previous item in a combo box. Note: If you use Freedom Scientific JAWA or other screen reader programs, then you must first disable the virtual PC cursor before using keystroke combinations to navigate the dashboard. You must enable the virtual PC cursor at other times, such as when navigating within table objects on a dashboard. Navigating with Keystrokes You can navigate with keystrokes on the Home page and in dashboards. Topics: Navigating on the Home Page Navigating in Dashboards Accessibility E-3

Navigating with Keystrokes Navigating on the Home Page The Home page is displayed when you sign in to Oracle BI Cloud Service or navigate from a different location. To navigate on the Home page with keystrokes: 1. Sign in to Oracle BI Cloud Service. 2. Press Control+Alt+G to display the Skip to Content link in the upper-left corner of the Home page. 3. Press an appropriate key. Keyboard Shortcut Enter Tab Result Navigate to the default starting location on the Home page. This location is the first link in the upper-left corner under the global header. Navigates to the first focusable element in the global header. Navigating in Dashboards 4. Continue to press Tab to navigate through the elements on the Home page. You can use keystrokes to navigate in dashboards. The following procedure describes one way to navigate a dashboard by using keyboard shortcuts. This procedure is an example; it does not include all keyboard shortcuts and options. To navigate in dashboards with keystrokes: 1. Sign in to Oracle BI Cloud Service, then take the appropriate action: Display If the Home page is displayed If a dashboard is displayed Action Then use keystrokes to display the dashboard. Press Control+Alt+D to navigate to the Dashboards menu in the global header. Press Enter to display the menu. Press Tab or the arrow keys to navigate through the dashboard names. Press Enter on the name of the dashboard to display it Proceed to the next step. Then proceed to the next step. 2. Navigate to the dashboard page: a. Press Control+Alt+G to display the Skip to Content link. b. Press Tab multiple times to navigate through the global header. Find the tab that corresponds to the first page of the dashboard. If there are no page tabs, then navigate to the first focusable element on the dashboard page. Press Tab to move through the dashboard pages. After the last page, pressing Tab gives focus to the dashboard page menu. c. Press Enter when the focus is on the appropriate page tab to open that page of the dashboard. E-4 Using Oracle Business Intelligence Cloud Service

Navigating with Keystrokes 3. Press Control+Shift+S to navigate to the first focusable element in the next section: the collapse icon. 4. Press Tab to navigate to the next focusable element in the current section. 5. Press Control+Shift+S to navigate to the first focusable element in the next section. 6. While the section collapse and expand icon has focus, press Enter to collapse the current section. 7. To navigate in a table or pivot table: a. Press Tab to select the table. b. Press Tab to move through table headers and to select any menus that exist there. c. When the table has focus, press the arrow keys to navigate among the columns and body cells of the table. To access the drop-down menus in the header rows when a body cell has focus, press Tab. Press Enter to display the options for the menu in the first header row. Press Tab and use the arrow keys to highlight the options. Press Enter to select the desired option. Accessibility E-5