Data Discovery, Analytics, and the Enterprise Data Hub

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Data Discovery, Analytics, and the Enterprise Data Hub"

Transcription

1 Data Discovery, Analytics, and the Enterprise Data Hub Version: 101

2 Table of Contents Summary 3 Used Data and Limitations of Legacy Analytic Architecture 3 The Meaning of Data Discovery & Analytics 4 Machine Learning in Data Discovery and Analytics 5 Conclusion 5 About the Author 5 2

3 We think too small, like the frog at the bottom of the well. He thinks the sky is only as big as the top of the well. If he surfaced, he would have an entirely different view. -Mao Zedong Summary There are two kinds of reporting and analytical environments in organizations today. Until recently, most organizations provided structured, cleansed and integrated data, summarized at levels convenient for conventional platforms. Data Warehousing and Business Intelligence dominate in these architectures. Other organizations, notably those that are primarily internet-centric, developed alternative ways to manage and analyze very large amounts of data from their own websites, search engines, and social physics (the analysis of external data from social media), now generally referred to as big data. Only in the latter case can true data discovery and analytics be enabled, but the tools and techniques of big data are rapidly becoming the accepted architecture in organizations. Used Data and Limitations of Legacy Analytic Architecture Operational Systems typically support a constrained set of functions, even if that set is vast, such as an ERP system. Data is captured and stored in a logical way that fits the functions of the system, often in structures and semantics that are understandable only to those familiar with the system internals. Many systems provide only perfunctory reporting and, of course, do not provide integration of their data with other systems. In most cases, it is not feasible to access this data directly for reporting and analytical purposes because: Analytical queries tend to be large and can affect performance of the system There are security issues that are typically enforced through the application software and could be compromised by direct access to the data Performance is critical in operational systems; therefore physical design of databases favor performance over separation from the application logic making retrieval difficult Most analytical work involves working with data from more than one operational system. Abstraction techniques that provide a single view of multiple data structures such as federation/virtualization have proven (with the current technology) to perform poorly and are difficult to set up and maintain For those reasons, there is always a need to work with secondhand or used data for purposes that go beyond the operational system. For example, a system may keep track of inventory and contractual compliance, but linking this information with financial information to determine customer profitability is not possible. This was the reason that Decision Support Systems (DSS), data warehouses, and Business Intelligence emerged. They provide tools for knowledge workers to access information from various systems to support all of their needs and processes. But the gathering of all of the data never really happens as previous technologies are too costly and not agile enough to handle the scale and variety of data that is needed today. An enterprise data hub (EDH), provides not only a cost-effective container of big data, it supports a myriad of tools and applications to optimize your use and understanding of data. Those who deal with used data have a need to discover and analyze information by formulating queries to discover patterns or underlying relationships in the data. This process spans multiple systems and operations. These interrogations and discoveries can take many forms from simple data set discovery with search, to point-and-click queries, to machine learning and esoteric ensemble techniques. But the platforms and data stores they use must mask the scale and complexity of the data, allowing the knowledge workers to seamlessly pursue their thought process and not have their productivity dragged down by platforms, tools, and approaches. 3 Unfortunately, old habits die hard. When it comes to BI, the industry is largely constrained by a drag of technology. What passes as acceptable BI in organizations today is rarely much more than re-platforming reports and queries that are ten- to twenty-years old. For analytics and BI to truly pay off in organizations, IT needs to shift its focus from deciding the informational needs of the organization through technical architecture and discipline, to one of responding to those needs as quickly as they arise by creating an agile data environment.

4 The Meaning of Data Discovery & Analytics This is the meaning of Data Discovery & Analytics rather than pre-arranging data and structures to address known informational needs; data discovery and analytics involves the combination of massive repositories of all kinds of data with the tools and computing power enabling knowledge workers to find patterns, build models, and create new value from used data. Not just data from an organization s operational system, but all forms of external data as well. Big data opened up the possibility of managing Social Physics, the ability to capture and use data from social media and a host of other non-traditional data sources. What does the term Data Discovery mean in today s landscape of tools and services? It is an imprecise term, but the industry adopted it, despite its often various meanings. Even the word discovery is a little misleading. Discovering data is not the desired outcome it is just one step in the process. Discovering an insight that leads to value is the main point of Data Discovery. The term arose as an alternative to highly structured business intelligence. This approach provides the ability to explore and analyze data more or less free of the constraining models of data warehouses and other data sources. With a Data Hub, analysts can use tools that profile data sources in the EDH. These tools include machine learning applications to automate the search for interesting patterns and correlations that are not obvious with the volumes and variety of data now available. Beyond the initial efforts; analysts filter, transform, clean, enrich, and manipulate the data, all without pre-designed structures and queries (though there are many situations where that is necessary and appropriate). What can you expect to see in Data Discovery and Analytics mode in an EDH? In a collaborative environment, it is typical for analysts to create new data in the hub, such as: Predictions, time series, descriptions (metadata) and narratives of their investigations Derived and blended data from existing data sets never before seen including additional attributes adding richness to the data Predictive models and other codes for quantitative analysis. These iterative data sets were once ignored due to the scarcity of storage space and rigid nature of systems. Data Hub s built on Hadoop have solved this by enabling: Larger sample sizes to create a complete view Access archived/historic data because of linear scalability of Hadoop Access to full fidelity data so that adding a new dimensions doesn t take months A system with integrated search/ SQL/ machine learning capabilities instead of just SQL Ability to reduce data preparation time through parallel processing In addition to data itself, the data discovery process is enhanced by tools and insights in what is generally an iterative and ongoing process: Weather data Rules engines and decision models Recommendation engines, both developed and licensed Broad quantitative tools including statistics Streaming data capture and real-time analysis Graphing/Charting tools 4

5 Machine Learning in Data Discovery and Analytics There are two primary techniques for data discovery: manual development of queries and guided or unguided machine learning. In the latter case, data scientists can provide various parameters to a machine learning algorithm, but as long as there is a person seeding the algorithms there is the problem of unintentional bias. This issue is more pronounced when the specialists are more informed about the tools than about the domain they are examining. The preferred method for minimizing the risk of introducing bias is during the detection phase of machine learning. Data scientists can then analyze the output of the machine learning process for patterns, issues and anomalies that are still best observed by a person, not a machine. The Hadoop ecosystem enables critical and highly sophisticated analytic algorithms to be applied in the background. This allows users to find or predict issues by sifting through enormous amounts of heterogeneous data minimizing bias, elapsed time, and excessive false positives. The goal of unattended machine learning is to derive useful, accurate and timely results for a wide range of requirements and investigations without much manual intervention. Data scientists are a scarce commodity, and anything that can make them more productive can reduce the costs (and error) of data discovery by replacing expensive development efforts with packaged algorithms. The EDH provides a single source of data, relieving the data scientists from extracting and cataloging many data sources for each analytic model. It provides not only access to the data, but can employ metadata schemes to make identifying and using the data in the EDH far simpler and less error-prone. And finally, there is a growing and already robust set of analytical tools that work directly with the EDH, efficiently. Conclusion The adoption of analytics will move an organization s efforts from simply informing decisions to taking action and tracking the effectiveness of those actions, thereby closing the loop. A giant leap in analytics is possible with the implementation of a modern architecture for managing and analyzing a broad collection of data with a rapidly developing community of tools and methods. About the Author Neil Raden, based in Santa Fe, NM, is an industry analyst and active consultant, widely published author and speaker and the founder of Hired Brains Research LLC, Hired Brains provides research, advisory and consulting services in Analytics, Big Data, and Decision Management for clients worldwide. Neil is also the co-author of the Dresner Advisory Services Wisdom of BI series on Advanced and Predictive Analytics. Neil was a contributing author to one of the first (1995) books on designing data warehouses and he is more recently the co-author of Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions, Prentice-Hall. He is a contributor to publications such as Wall Street Week, Forbes, Information Week and ComputerWorld. He welcomes your comments at or his blog at 5

6 About Cloudera Cloudera is revolutionizing enterprise data management by offering the first unified Platform for big data, an enterprise data hub built on Apache Hadoop. Cloudera offers enterprises one place to store, access, process, secure, and analyze all their data, empowering them to extend the value of existing investments while enabling fundamental new ways to derive value from their data. Cloudera s open source big data platform is the most widely adopted in the world, and Cloudera is the most prolific contributor to the open source Hadoop ecosystem. As the leading educator of Hadoop professionals, Cloudera has trained over 22,000 individuals worldwide. Over 1,400 partners and a seasoned professional services team help deliver greater time to value. Finally, only Cloudera provides proactive and predictive support to run an enterprise data hub with confidence. Leading organizations in every industry plus top public sector organizations globally run Cloudera in production. For additional information, please visit us at: cloudera.com or Cloudera, Inc Page Mill Road, Palo Alto, CA 94304, USA 2015 Cloudera, Inc. All rights reserved. Cloudera and the Cloudera logo are trademarks or registered trademarks of Cloudera Inc. in the USA and other countries. All other trademarks are the property of their respective companies. Information is subject to change without notice.

Operational Analytics

Operational Analytics Operational Analytics Version: 101 Table of Contents Operational Analytics 3 From the Enterprise Data Hub to the Enterprise Application Hub 3 Operational Intelligence in Action: Some Examples 4 Requirements

More information

An Enterprise Data Hub, the Next Gen Operational Data Store

An Enterprise Data Hub, the Next Gen Operational Data Store An Enterprise Data Hub, the Next Gen Operational Data Store Version: 101 Table of Contents Summary 3 The ODS in Practice 4 Drawbacks of the ODS Today 5 The Case for ODS on an EDH 5 Conclusion 6 About the

More information

INDUSTRY BRIEF DATA CONSOLIDATION AND MULTI-TENANCY IN FINANCIAL SERVICES

INDUSTRY BRIEF DATA CONSOLIDATION AND MULTI-TENANCY IN FINANCIAL SERVICES INDUSTRY BRIEF DATA CONSOLIDATION AND MULTI-TENANCY IN FINANCIAL SERVICES Data Consolidation and Multi-Tenancy in Financial Services CLOUDERA INDUSTRY BRIEF 2 Table of Contents Introduction 3 Security

More information

Cloudera Enterprise Data Hub in Telecom:

Cloudera Enterprise Data Hub in Telecom: Cloudera Enterprise Data Hub in Telecom: Three Customer Case Studies Version: 103 Table of Contents Introduction 3 Cloudera Enterprise Data Hub for Telcos 4 Cloudera Enterprise Data Hub in Telecom: Customer

More information

locuz.com Big Data Services

locuz.com Big Data Services locuz.com Big Data Services Big Data At Locuz, we help the enterprise move from being a data-limited to a data-driven one, thereby enabling smarter, faster decisions that result in better business outcome.

More information

Deploying an Operational Data Store Designed for Big Data

Deploying an Operational Data Store Designed for Big Data Deploying an Operational Data Store Designed for Big Data A fast, secure, and scalable data staging environment with no data volume or variety constraints Sponsored by: Version: 102 Table of Contents Introduction

More information

Accelerate your Big Data Strategy. Execute faster with Capgemini and Cloudera s Enterprise Data Hub Accelerator

Accelerate your Big Data Strategy. Execute faster with Capgemini and Cloudera s Enterprise Data Hub Accelerator Accelerate your Big Data Strategy Execute faster with Capgemini and Cloudera s Enterprise Data Hub Accelerator Enterprise Data Hub Accelerator enables you to get started rapidly and cost-effectively with

More information

Integrating Cloudera and SAP HANA

Integrating Cloudera and SAP HANA Integrating Cloudera and SAP HANA Version: 103 Table of Contents Introduction/Executive Summary 4 Overview of Cloudera Enterprise 4 Data Access 5 Apache Hive 5 Data Processing 5 Data Integration 5 Partner

More information

www.ducenit.com Analance Data Integration Technical Whitepaper

www.ducenit.com Analance Data Integration Technical Whitepaper Analance Data Integration Technical Whitepaper Executive Summary Business Intelligence is a thriving discipline in the marvelous era of computing in which we live. It s the process of analyzing and exploring

More information

Driving Growth in Insurance With a Big Data Architecture

Driving Growth in Insurance With a Big Data Architecture Driving Growth in Insurance With a Big Data Architecture The SAS and Cloudera Advantage Version: 103 Table of Contents Overview 3 Current Data Challenges for Insurers 3 Unlocking the Power of Big Data

More information

UNLEASHING THE VALUE OF THE TERADATA UNIFIED DATA ARCHITECTURE WITH ALTERYX

UNLEASHING THE VALUE OF THE TERADATA UNIFIED DATA ARCHITECTURE WITH ALTERYX UNLEASHING THE VALUE OF THE TERADATA UNIFIED DATA ARCHITECTURE WITH ALTERYX 1 Successful companies know that analytics are key to winning customer loyalty, optimizing business processes and beating their

More information

www.sryas.com Analance Data Integration Technical Whitepaper

www.sryas.com Analance Data Integration Technical Whitepaper Analance Data Integration Technical Whitepaper Executive Summary Business Intelligence is a thriving discipline in the marvelous era of computing in which we live. It s the process of analyzing and exploring

More information

Data Catalogs for Hadoop Achieving Shared Knowledge and Re-usable Data Prep. Neil Raden Hired Brains Research, LLC

Data Catalogs for Hadoop Achieving Shared Knowledge and Re-usable Data Prep. Neil Raden Hired Brains Research, LLC Data Catalogs for Hadoop Achieving Shared Knowledge and Re-usable Data Prep Neil Raden Hired Brains Research, LLC Traditionally, the job of gathering and integrating data for analytics fell on data warehouses.

More information

Integrate and Deliver Trusted Data and Enable Deep Insights

Integrate and Deliver Trusted Data and Enable Deep Insights SAP Technical Brief SAP s for Enterprise Information Management SAP Data Services Objectives Integrate and Deliver Trusted Data and Enable Deep Insights Provide a wide-ranging view of enterprise information

More information

Empowering the Masses with Analytics

Empowering the Masses with Analytics Empowering the Masses with Analytics THE GAP FOR BUSINESS USERS For a discussion of bridging the gap from the perspective of a business user, read Three Ways to Use Data Science. Ask the average business

More information

Bringing Strategy to Life Using an Intelligent Data Platform to Become Data Ready. Informatica Government Summit April 23, 2015

Bringing Strategy to Life Using an Intelligent Data Platform to Become Data Ready. Informatica Government Summit April 23, 2015 Bringing Strategy to Life Using an Intelligent Platform to Become Ready Informatica Government Summit April 23, 2015 Informatica Solutions Overview Power the -Ready Enterprise Government Imperatives Improve

More information

Unleash your intuition

Unleash your intuition Introducing Qlik Sense Unleash your intuition Qlik Sense is a next-generation self-service data visualization application that empowers everyone to easily create a range of flexible, interactive visualizations

More information

Oracle Big Data Discovery The Visual Face of Hadoop

Oracle Big Data Discovery The Visual Face of Hadoop Disclaimer: This document is for informational purposes. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development,

More information

More Data in Less Time

More Data in Less Time More Data in Less Time Leveraging Cloudera CDH as an Operational Data Store Daniel Tydecks, Systems Engineering DACH & CE Goals of an Operational Data Store Load Data Sources Traditional Architecture Operational

More information

Three Open Blueprints For Big Data Success

Three Open Blueprints For Big Data Success White Paper: Three Open Blueprints For Big Data Success Featuring Pentaho s Open Data Integration Platform Inside: Leverage open framework and open source Kickstart your efforts with repeatable blueprints

More information

Delivering Smart Answers!

Delivering Smart Answers! Companion for SharePoint Topic Analyst Companion for SharePoint All Your Information Enterprise-ready Enrich SharePoint, your central place for document and workflow management, not only with an improved

More information

Ignite Your Creative Ideas with Fast and Engaging Data Discovery

Ignite Your Creative Ideas with Fast and Engaging Data Discovery SAP Brief SAP BusinessObjects BI s SAP Crystal s SAP Lumira Objectives Ignite Your Creative Ideas with Fast and Engaging Data Discovery Tap into your data big and small Tap into your data big and small

More information

Data Doesn t Communicate Itself Using Visualization to Tell Better Stories

Data Doesn t Communicate Itself Using Visualization to Tell Better Stories SAP Brief Analytics SAP Lumira Objectives Data Doesn t Communicate Itself Using Visualization to Tell Better Stories Tap into your data big and small Tap into your data big and small In today s fast-paced

More information

Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora

Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora SAP Brief SAP Technology SAP HANA Vora Objectives Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora Bridge the divide between enterprise data and Big Data Bridge the divide

More information

Qlik Sense Enterprise

Qlik Sense Enterprise Data Sheet Qlik Sense Enterprise See the whole story that lives within your data Qlik Sense is a next-generation visual analytics platform that empowers everyone to see the whole story that lives within

More information

Analytics With Hadoop. SAS and Cloudera Starter Services: Visual Analytics and Visual Statistics

Analytics With Hadoop. SAS and Cloudera Starter Services: Visual Analytics and Visual Statistics Analytics With Hadoop SAS and Cloudera Starter Services: Visual Analytics and Visual Statistics Everything You Need to Get Started on Your First Hadoop Project SAS and Cloudera have identified the essential

More information

Safe Harbor Statement

Safe Harbor Statement Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment

More information

Datenverwaltung im Wandel - Building an Enterprise Data Hub with

Datenverwaltung im Wandel - Building an Enterprise Data Hub with Datenverwaltung im Wandel - Building an Enterprise Data Hub with Cloudera Bernard Doering Regional Director, Central EMEA, Cloudera Cloudera Your Hadoop Experts Founded 2008, by former employees of Employees

More information

Customer Insight Appliance. Enabling retailers to understand and serve their customer

Customer Insight Appliance. Enabling retailers to understand and serve their customer Customer Insight Appliance Enabling retailers to understand and serve their customer Customer Insight Appliance Enabling retailers to understand and serve their customer. Technology has empowered today

More information

The Enterprise Data Hub and The Modern Information Architecture

The Enterprise Data Hub and The Modern Information Architecture The Enterprise Data Hub and The Modern Information Architecture Dr. Amr Awadallah CTO & Co-Founder, Cloudera Twitter: @awadallah 1 2013 Cloudera, Inc. All rights reserved. Cloudera Overview The Leader

More information

Hadoop Data Hubs and BI. Supporting the migration from siloed reporting and BI to centralized services with Hadoop

Hadoop Data Hubs and BI. Supporting the migration from siloed reporting and BI to centralized services with Hadoop Hadoop Data Hubs and BI Supporting the migration from siloed reporting and BI to centralized services with Hadoop John Allen October 2014 Introduction John Allen; computer scientist Background in data

More information

The Top Challenges in Big Data and Analytics

The Top Challenges in Big Data and Analytics Big Data Leads to Insights, Improvements & Automation Over the past few years, there has been a tremendous amount of hype around Big Data data that doesn t work well in traditional BI systems and warehouses

More information

ENHANCING INTELLIGENCE SUCCESS: DATA CHARACTERIZATION Francine Forney, Senior Management Consultant, Fuel Consulting, LLC May 2013

ENHANCING INTELLIGENCE SUCCESS: DATA CHARACTERIZATION Francine Forney, Senior Management Consultant, Fuel Consulting, LLC May 2013 ENHANCING INTELLIGENCE SUCCESS: DATA CHARACTERIZATION, Fuel Consulting, LLC May 2013 DATA AND ANALYSIS INTERACTION Understanding the content, accuracy, source, and completeness of data is critical to the

More information

PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309

PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309 PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309 It s going mainstream, and it s your next opportunity. by Merv Adrian Enterprises have never had more data, and it s no surprise

More information

Databricks. A Primer

Databricks. A Primer Databricks A Primer Who is Databricks? Databricks vision is to empower anyone to easily build and deploy advanced analytics solutions. The company was founded by the team who created Apache Spark, a powerful

More information

Navigating Big Data business analytics

Navigating Big Data business analytics mwd a d v i s o r s Navigating Big Data business analytics Helena Schwenk A special report prepared for Actuate May 2013 This report is the third in a series and focuses principally on explaining what

More information

White Paper: Enhancing Functionality and Security of Enterprise Data Holdings

White Paper: Enhancing Functionality and Security of Enterprise Data Holdings White Paper: Enhancing Functionality and Security of Enterprise Data Holdings Examining New Mission- Enabling Design Patterns Made Possible by the Cloudera- Intel Partnership Inside: Improving Return on

More information

Oracle Big Data Discovery Unlock Potential in Big Data Reservoir

Oracle Big Data Discovery Unlock Potential in Big Data Reservoir Oracle Big Data Discovery Unlock Potential in Big Data Reservoir Gokula Mishra Premjith Balakrishnan Business Analytics Product Group September 29, 2014 Copyright 2014, Oracle and/or its affiliates. All

More information

Using Tableau Software with Hortonworks Data Platform

Using Tableau Software with Hortonworks Data Platform Using Tableau Software with Hortonworks Data Platform September 2013 2013 Hortonworks Inc. http:// Modern businesses need to manage vast amounts of data, and in many cases they have accumulated this data

More information

Visualization Starter Pack from SAP Overview Enabling Self-Service Data Exploration and Visualization

Visualization Starter Pack from SAP Overview Enabling Self-Service Data Exploration and Visualization Business Intelligence Visualization Starter Pack from SAP Overview Enabling Self-Service Data Exploration and Visualization In today s environment, almost every corporation has to work with enormous data

More information

High-Performance Business Analytics: SAS and IBM Netezza Data Warehouse Appliances

High-Performance Business Analytics: SAS and IBM Netezza Data Warehouse Appliances High-Performance Business Analytics: SAS and IBM Netezza Data Warehouse Appliances Highlights IBM Netezza and SAS together provide appliances and analytic software solutions that help organizations improve

More information

How Master Data Management powers big data decision making.

How Master Data Management powers big data decision making. decision ready. How Master Data Management powers big data decision making. Building an enterprise architecture that s decision ready. Bringing discipline to big data. The trouble with insight is it doesn

More information

DATAOPT SOLUTIONS. What Is Big Data?

DATAOPT SOLUTIONS. What Is Big Data? DATAOPT SOLUTIONS What Is Big Data? WHAT IS BIG DATA? It s more than just large amounts of data, though that s definitely one component. The more interesting dimension is about the types of data. So Big

More information

Agile Business Intelligence Data Lake Architecture

Agile Business Intelligence Data Lake Architecture Agile Business Intelligence Data Lake Architecture TABLE OF CONTENTS Introduction... 2 Data Lake Architecture... 2 Step 1 Extract From Source Data... 5 Step 2 Register And Catalogue Data Sets... 5 Step

More information

White Paper: SAS and Apache Hadoop For Government. Inside: Unlocking Higher Value From Business Analytics to Further the Mission

White Paper: SAS and Apache Hadoop For Government. Inside: Unlocking Higher Value From Business Analytics to Further the Mission White Paper: SAS and Apache Hadoop For Government Unlocking Higher Value From Business Analytics to Further the Mission Inside: Using SAS and Hadoop Together Design Considerations for Your SAS and Hadoop

More information

MDM and Data Warehousing Complement Each Other

MDM and Data Warehousing Complement Each Other Master Management MDM and Warehousing Complement Each Other Greater business value from both 2011 IBM Corporation Executive Summary Master Management (MDM) and Warehousing (DW) complement each other There

More information

The Definitive Guide to Data Blending. White Paper

The Definitive Guide to Data Blending. White Paper The Definitive Guide to Data Blending White Paper Leveraging Alteryx Analytics for data blending you can: Gather and blend data from virtually any data source including local, third-party, and cloud/ social

More information

White Paper: Datameer s User-Focused Big Data Solutions

White Paper: Datameer s User-Focused Big Data Solutions CTOlabs.com White Paper: Datameer s User-Focused Big Data Solutions May 2012 A White Paper providing context and guidance you can use Inside: Overview of the Big Data Framework Datameer s Approach Consideration

More information

Cloudera in the Public Cloud

Cloudera in the Public Cloud Cloudera in the Public Cloud Deployment Options for the Enterprise Data Hub Version: Q414-102 Table of Contents Executive Summary 3 The Case for Public Cloud 5 Public Cloud vs On-Premise 6 Public Cloud

More information

Delivering information you can trust December IBM Information Server FastTrack: The need for speed accelerating data integration projects

Delivering information you can trust December IBM Information Server FastTrack: The need for speed accelerating data integration projects December 2007 IBM Information Server FastTrack: The need for speed accelerating data integration projects Page 2 Contents 3 Creating a collaborative development environment 5 Optimizing data integration

More information

The IBM Cognos Platform for Enterprise Business Intelligence

The IBM Cognos Platform for Enterprise Business Intelligence The IBM Cognos Platform for Enterprise Business Intelligence Highlights Optimize performance with in-memory processing and architecture enhancements Maximize the benefits of deploying business analytics

More information

Enterprise Resource Planning Analysis of Business Intelligence & Emergence of Mining Objects

Enterprise Resource Planning Analysis of Business Intelligence & Emergence of Mining Objects Enterprise Resource Planning Analysis of Business Intelligence & Emergence of Mining Objects Abstract: Build a model to investigate system and discovering relations that connect variables in a database

More information

White Paper. Thirsting for Insight? Quench It With 5 Data Management for Analytics Best Practices.

White Paper. Thirsting for Insight? Quench It With 5 Data Management for Analytics Best Practices. White Paper Thirsting for Insight? Quench It With 5 Data Management for Analytics Best Practices. Contents Data Management: Why It s So Essential... 1 The Basics of Data Preparation... 1 1: Simplify Access

More information

Why Big Data? Why Now?

Why Big Data? Why Now? Ellis Holman Why Big Data? Why Now? Information is at the Center of a New Wave of Opportunity 44x as much Data and Content Over Coming Decade 2020 35 zettabytes And Organizations Need Deeper Insights 1in3

More information

Understanding Your Customer Journey by Extending Adobe Analytics with Big Data

Understanding Your Customer Journey by Extending Adobe Analytics with Big Data SOLUTION BRIEF Understanding Your Customer Journey by Extending Adobe Analytics with Big Data Business Challenge Today s digital marketing teams are overwhelmed by the volume and variety of customer interaction

More information

Enterprise Data Integration

Enterprise Data Integration Enterprise Data Integration Access, Integrate, and Deliver Data Efficiently Throughout the Enterprise brochure How Can Your IT Organization Deliver a Return on Data? The High Price of Data Fragmentation

More information

Integrating a Big Data Platform into Government:

Integrating a Big Data Platform into Government: Integrating a Big Data Platform into Government: Drive Better Decisions for Policy and Program Outcomes John Haddad, Senior Director Product Marketing, Informatica Digital Government Institute s Government

More information

www.pwc.com Implementation of Big Data and Analytics Projects with Big Data Discovery and BICS March 2015

www.pwc.com Implementation of Big Data and Analytics Projects with Big Data Discovery and BICS March 2015 www.pwc.com Implementation of Big Data and Analytics Projects with Big Data Discovery and BICS Agenda Big Data Discovery Oracle Business Intelligence Cloud Services (BICS) Use Cases How to start and our

More information

JOURNAL OF OBJECT TECHNOLOGY

JOURNAL OF OBJECT TECHNOLOGY JOURNAL OF OBJECT TECHNOLOGY Online at www.jot.fm. Published by ETH Zurich, Chair of Software Engineering JOT, 2008 Vol. 7, No. 8, November-December 2008 What s Your Information Agenda? Mahesh H. Dodani,

More information

ENTERPRISE BI AND DATA DISCOVERY, FINALLY

ENTERPRISE BI AND DATA DISCOVERY, FINALLY Enterprise-caliber Cloud BI ENTERPRISE BI AND DATA DISCOVERY, FINALLY Southard Jones, Vice President, Product Strategy 1 AGENDA Market Trends Cloud BI Market Surveys Visualization, Data Discovery, & Self-Service

More information

CONNECTING DATA WITH BUSINESS

CONNECTING DATA WITH BUSINESS CONNECTING DATA WITH BUSINESS Big Data and Data Science consulting Business Value through Data Knowledge Synergic Partners is a specialized Big Data, Data Science and Data Engineering consultancy firm

More information

Apache Hadoop in the Enterprise. Dr. Amr Awadallah, CTO/Founder @awadallah, aaa@cloudera.com

Apache Hadoop in the Enterprise. Dr. Amr Awadallah, CTO/Founder @awadallah, aaa@cloudera.com Apache Hadoop in the Enterprise Dr. Amr Awadallah, CTO/Founder @awadallah, aaa@cloudera.com Cloudera The Leader in Big Data Management Powered by Apache Hadoop The Leading Open Source Distribution of Apache

More information

A Reference Architecture for Next Generation Big Data and Analytics

A Reference Architecture for Next Generation Big Data and Analytics A Reference Architecture for Next Generation Big Data and Analytics A Reference Architecture for Next Generation Big Data and Analytics 2 CONTENTS Executive Summary 3 Introduction 4 Current State of Hadoop

More information

Information-Driven Transformation in Retail with the Enterprise Data Hub Accelerator

Information-Driven Transformation in Retail with the Enterprise Data Hub Accelerator Introduction Enterprise Data Hub Accelerator Retail Sector Use Cases Capabilities Information-Driven Transformation in Retail with the Enterprise Data Hub Accelerator Introduction Enterprise Data Hub Accelerator

More information

The Business Analyst s Guide to Hadoop

The Business Analyst s Guide to Hadoop White Paper The Business Analyst s Guide to Hadoop Get Ready, Get Set, and Go: A Three-Step Guide to Implementing Hadoop-based Analytics By Alteryx and Hortonworks (T)here is considerable evidence that

More information

WHITE PAPER. Data to Diamonds Delivering valuable business insights

WHITE PAPER. Data to Diamonds Delivering valuable business insights WHITE PAPER Data to Diamonds Delivering valuable business insights In a world of uncertainty and economic challenges, data and analytics have become critical to survive. The importance of monitoring and

More information

machine data analytics drive new values

machine data analytics drive new values how glassbeam is driving internet of things machine data innovation machine data analytics drive new values February 2016 technology innovator perspective Harbor Research Glassbeam recently announced two

More information

Scalable Enterprise Data Integration Your business agility depends on how fast you can access your complex data

Scalable Enterprise Data Integration Your business agility depends on how fast you can access your complex data Transforming Data into Intelligence Scalable Enterprise Data Integration Your business agility depends on how fast you can access your complex data Big Data Data Warehousing Data Governance and Quality

More information

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP Pythian White Paper TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP ABSTRACT As companies increasingly rely on big data to steer decisions, they also find themselves looking for ways to simplify

More information

Enterprise Information Catalog. Self Service Data Discovery through Enterprise Information Catalog

Enterprise Information Catalog. Self Service Data Discovery through Enterprise Information Catalog Enterprise Information Catalog Self Service Data Discovery through Enterprise Information Catalog Safe Harbor The information being provided today is for informational purposes only. The development, release

More information

W H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract

W H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract W H I T E P A P E R Deriving Intelligence from Large Data Using Hadoop and Applying Analytics Abstract This white paper is focused on discussing the challenges facing large scale data processing and the

More information

BIG DATA & ANALYTICS. Transforming the business and driving revenue through big data and analytics

BIG DATA & ANALYTICS. Transforming the business and driving revenue through big data and analytics BIG DATA & ANALYTICS Transforming the business and driving revenue through big data and analytics Collection, storage and extraction of business value from data generated from a variety of sources are

More information

Five Reasons Spotfire Is Better than Excel for Business Data Analytics

Five Reasons Spotfire Is Better than Excel for Business Data Analytics Five Reasons Spotfire Is Better than Excel for Business Data Analytics A hugely versatile application, Microsoft Excel is the Swiss Army Knife of IT, able to cope with all kinds of jobs from managing personal

More information

Are You Big Data Ready?

Are You Big Data Ready? ACS 2015 Annual Canberra Conference Are You Big Data Ready? Vladimir Videnovic Business Solutions Director Oracle Big Data and Analytics Introduction Introduction What is Big Data? If you can't explain

More information

IBM Analytics. Just the facts: Four critical concepts for planning the logical data warehouse

IBM Analytics. Just the facts: Four critical concepts for planning the logical data warehouse IBM Analytics Just the facts: Four critical concepts for planning the logical data warehouse 1 2 3 4 5 6 Introduction Complexity Speed is businessfriendly Cost reduction is crucial Analytics: The key to

More information

Making confident decisions with the full spectrum of analysis capabilities

Making confident decisions with the full spectrum of analysis capabilities IBM Software Business Analytics Analysis Making confident decisions with the full spectrum of analysis capabilities Making confident decisions with the full spectrum of analysis capabilities Contents 2

More information

How CFOs and their teams are supercharging financial reporting

How CFOs and their teams are supercharging financial reporting How CFOs and their teams are supercharging financial reporting Are your finance operations running smoothly? Today s Chief Finance Officers have an opportunity to take a more visible role in strategic

More information

REAL-TIME OPERATIONAL INTELLIGENCE. Competitive advantage from unstructured, high-velocity log and machine Big Data

REAL-TIME OPERATIONAL INTELLIGENCE. Competitive advantage from unstructured, high-velocity log and machine Big Data REAL-TIME OPERATIONAL INTELLIGENCE Competitive advantage from unstructured, high-velocity log and machine Big Data 2 SQLstream: Our s-streaming products unlock the value of high-velocity unstructured log

More information

Five Technology Trends for Improved Business Intelligence Performance

Five Technology Trends for Improved Business Intelligence Performance TechTarget Enterprise Applications Media E-Book Five Technology Trends for Improved Business Intelligence Performance The demand for business intelligence data only continues to increase, putting BI vendors

More information

IBM AND NEXT GENERATION ARCHITECTURE FOR BIG DATA & ANALYTICS!

IBM AND NEXT GENERATION ARCHITECTURE FOR BIG DATA & ANALYTICS! The Bloor Group IBM AND NEXT GENERATION ARCHITECTURE FOR BIG DATA & ANALYTICS VENDOR PROFILE The IBM Big Data Landscape IBM can legitimately claim to have been involved in Big Data and to have a much broader

More information

Why Big Data Analytics?

Why Big Data Analytics? An ebook by Datameer Why Big Data Analytics? Three Business Challenges Best Addressed Using Big Data Analytics It s hard to overstate the importance of data for businesses today. It s the lifeline of any

More information

Capitalize on Big Data for Competitive Advantage with Bedrock TM, an integrated Management Platform for Hadoop Data Lakes

Capitalize on Big Data for Competitive Advantage with Bedrock TM, an integrated Management Platform for Hadoop Data Lakes Capitalize on Big Data for Competitive Advantage with Bedrock TM, an integrated Management Platform for Hadoop Data Lakes Highly competitive enterprises are increasingly finding ways to maximize and accelerate

More information

Database Marketing, Business Intelligence and Knowledge Discovery

Database Marketing, Business Intelligence and Knowledge Discovery Database Marketing, Business Intelligence and Knowledge Discovery Note: Using material from Tan / Steinbach / Kumar (2005) Introduction to Data Mining,, Addison Wesley; and Cios / Pedrycz / Swiniarski

More information

IBM Software Delivering trusted information for the modern data warehouse

IBM Software Delivering trusted information for the modern data warehouse Delivering trusted information for the modern data warehouse Make information integration and governance a best practice in the big data era Contents 2 Introduction In ever-changing business environments,

More information

INDUSTRY BRIEF THREE FACTORS ENTRENCHING BIG DATA IN FINANCIAL SERVICES

INDUSTRY BRIEF THREE FACTORS ENTRENCHING BIG DATA IN FINANCIAL SERVICES INDUSTRY BRIEF THREE FACTORS ENTRENCHING BIG DATA IN FINANCIAL SERVICES Three Factors Entrenching Big Data in Financial Services CLOUDERA INDUSTRY BRIEF 2 Table of Contents Introduction 3 Towards Competitive

More information

WHITEPAPER. A Data Analytics Plan: Do you have one? Five factors to consider on your analytics journey. www.inetco.com

WHITEPAPER. A Data Analytics Plan: Do you have one? Five factors to consider on your analytics journey. www.inetco.com A Data Analytics Plan: Do you have one? Five factors to consider on your analytics journey www.inetco.com Overview Both the technology operations and business side of your organization may be talking about

More information

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Oman College of Management and Technology Course 803401 DSS Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization CS/MIS Department Information Sharing

More information

Implementing a Data Warehouse with Microsoft SQL Server

Implementing a Data Warehouse with Microsoft SQL Server Course Code: M20463 Vendor: Microsoft Course Overview Duration: 5 RRP: 2,025 Implementing a Data Warehouse with Microsoft SQL Server Overview This course describes how to implement a data warehouse platform

More information

Solutions for Communications with IBM Netezza Network Analytics Accelerator

Solutions for Communications with IBM Netezza Network Analytics Accelerator Solutions for Communications with IBM Netezza Analytics Accelerator The all-in-one network intelligence appliance for the telecommunications industry Highlights The Analytics Accelerator combines speed,

More information

Accelerate BI Initiatives With Self-Service Data Discovery And Integration

Accelerate BI Initiatives With Self-Service Data Discovery And Integration A Custom Technology Adoption Profile Commissioned By Attivio June 2015 Accelerate BI Initiatives With Self-Service Data Discovery And Integration Introduction The rapid advancement of technology has ushered

More information

Cisco Data Preparation

Cisco Data Preparation Data Sheet Cisco Data Preparation Unleash your business analysts to develop the insights that drive better business outcomes, sooner, from all your data. As self-service business intelligence (BI) and

More information

From Lab to Factory: The Big Data Management Workbook

From Lab to Factory: The Big Data Management Workbook Executive Summary From Lab to Factory: The Big Data Management Workbook How to Operationalize Big Data Experiments in a Repeatable Way and Avoid Failures Executive Summary Businesses looking to uncover

More information

Data Warehouse design

Data Warehouse design Data Warehouse design Design of Enterprise Systems University of Pavia 21/11/2013-1- Data Warehouse design DATA PRESENTATION - 2- BI Reporting Success Factors BI platform success factors include: Performance

More information

Digital Business Platform for SAP

Digital Business Platform for SAP BUSINESS WHITE PAPER Digital Business Platform for SAP SAP ERP is the foundation on which the enterprise runs. Software AG adds the missing agility component with a digital business platform. CONTENT 1

More information

IBM Cognos Performance Management Solutions for Oracle

IBM Cognos Performance Management Solutions for Oracle IBM Cognos Performance Management Solutions for Oracle Gain more value from your Oracle technology investments Highlights Deliver the power of predictive analytics across the organization Address diverse

More information

Cloudera Enterprise Reference Architecture for Google Cloud Platform Deployments

Cloudera Enterprise Reference Architecture for Google Cloud Platform Deployments Cloudera Enterprise Reference Architecture for Google Cloud Platform Deployments Important Notice 2010-2015 Cloudera, Inc. All rights reserved. Cloudera, the Cloudera logo, Cloudera Impala, Impala, and

More information

VIEWPOINT. High Performance Analytics. Industry Context and Trends

VIEWPOINT. High Performance Analytics. Industry Context and Trends VIEWPOINT High Performance Analytics Industry Context and Trends In the digital age of social media and connected devices, enterprises have a plethora of data that they can mine, to discover hidden correlations

More information

COURSE 20463C: IMPLEMENTING A DATA WAREHOUSE WITH MICROSOFT SQL SERVER

COURSE 20463C: IMPLEMENTING A DATA WAREHOUSE WITH MICROSOFT SQL SERVER Page 1 of 8 ABOUT THIS COURSE This 5 day course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft SQL Server

More information

Enterprise Data Integration The Foundation for Business Insight

Enterprise Data Integration The Foundation for Business Insight Enterprise Data Integration The Foundation for Business Insight Data Hubs Data Migration Data Warehousing Data Synchronization Business Activity Monitoring Ingredients for Success Enterprise Visibility

More information