How To Build A Data Intelligence Platform

Transcription

1

2 Business Intelligence (BI) Added Value for Reporting & Analysis Copyright ibax AG October 2006

3 Table of Content Vision Power and Limitations Objectives Business Perspective Reporting & Analysis Economic Value Solution and Processing Components Business Intelligence Market Implementation Framework 3

4 Vision transfer data to knowledge DECISION KNOWLEDGE INFORMATION INFORMATION DATA DATA DATA Business intelligence describes the enterprise's ability to access data and explore information (often contained in a data warehouse) and to analyze that information to develop insights and understanding, which leads to improved and informed decision making. K. Harris, H. Dresner, Gartner Group 4

5 Business Intelligence power, limitations and integration POWER Data Integration & Consolidation of multiple sources and structures Reporting & Analysis of aggregated information transparent, consistent quality-improved, enriched high-performance data retrieval flexible, easy to use Information Platform to monitor processes and results to gain insights and understanding to support informed decision making LIMITATIONS Business Intelligence is NOT the recommended platform for transaction processing (date entry and modification) transaction based reporting (i.e.; billing) application/workflow business logic time-critical, computer-aided process control (i.e.; machinery) process individual complex calculations master data maintenance (.i.e. product catalogs) INTEGRATION Closed Loop (business intelligence platform with transactional systems) feed back of consolidated, quality-improved and enriched data used for integrated information lookup and data prediction context related work process integration of source system application with calling actions Context related integration of quantitative and qualitative information by front-end integration and synchronization of quantitative Business Intelligence data with Semantic Webs holding qualitative summable information (flow text, images, audio/video, etc.) 5

6 Objectives business perspective Corporate Information System Balanced Scorecard / Corporate Performance Measurement (CPM) Corporate Platform for fast and efficient Reporting & Analysis Enterprise Business Integration (Platforms and Data) Demand for single version of truth Data Integration to support corporate service-oriented architecture for Reporting & Analysis Combine and compare data from multiple sources Combine and merge catalogs (i.e.; global and local products) Persistent and unified sights of data structures and contents Reflect historical structural changes (organization, products, etc.) 6

7 Objectives business perspective (continued) Data Access Support of reporting and analysis requirements for all various user groups alike (content, layout, functionality, ad-hoc) Secure, high performance access with no impact on source system Cost Savings / Value Chain Integration Reduce labor-intensive report generation, avoid overlapping report efforts and requirement for individual programming Platform consolidation and automation minimizes costs of platform operations and maintenance Implement closed loop benefits (data quality, prediction models) Provide key suppliers/customers with value-added, individual reporting/analysis features accessing the BI platform 7

8 Reporting & Analysis business intelligence front-end platform advantage and Analysis Ad-hoc Reporting Interactivity Performance audience Business Analyst Report Explorer Report Reader EXAMPLE: ProClarity Product Platform ( ProClarity Desktop Professional (incl. KPI Designer / Selector and Excel Business Reporter) ProClarity Analytics Server (Web Server & Report Repository) ProClarity Dashboard Server / ProClarity Publishing Server Full Integration with Microsoft Business Intelligence Platform (incl. SharePoint Portal Server and Microsoft Office) 8

9 Economic Value BI as enabler to monitor/optimize value chain activities Purchase Production & Inventory Marketing & Sales Supplier Finance & Legal Profit Customer Human Resources Information Technology Primary Activities are the core activities of a company to create economic value and therefore must be monitored/benchmarked constantly (processes, resources, costs). Support Activities help the primary activities to realize their full potential and must follow the same rules as the primary activities regarding quality, in-time delivery, activity costs, etc. Business Intelligence Role Provide all users (management and staff) a unified, consistent sight with up-to-date, high-quality information covering their responsibilities. All users are able to monitor and investigate the root causes and dependencies for their KPIs accordingly. Committed corporate performance management with transparent processes and clear responsibilities and in equal measure best-practice use of information technology are the key drivers and enablers to improve the performance of all your activities and therefore to maximize its economic value. 9

10 Economic Value all activities are important AREA DEVELOPMENT in-time flexible extensible MANUFACTURING & TRADE pool purchase power minimize variety of base material maximize potential variety high re-usability of all components support cross-docking customer loyalty program INFORMATION TECHNOLOGY & BUSINESS INTELLIGENCE unified, open HW/SW platforms with standards for business applications and reporting & analysis flexible multi-source data integration master data management (of catalogs) single version of truth flexible source-independent reporting model OPERATION in-time in-cost optimize production planning streamline processes (kanban, etc.) full automation flexible/cost-efficient machinery optimize product/service assortment KPI monitoring user/business-centric report building user friendly interfaces to minimize costs for training and user support fully automated ETL & notification process data quality monitoring minimize operational costs To maximize the corporate economic value, all core activities must follow best-practice principles. Therefore also all supporting business intelligence activities must follow best-practice principles to be able to provide high-quality information in-time at sustainable low operational costs. 10

11 Solution Components as used to build a sustainable BI platform ALWAYS (!) REQUIRED OPTION: DATA WAREHOUSE or DATA MART OPTION: OLAP CUBES project management and communication specification of report & analysis needs (content, structure, KPI, scorecard) metadata repository (incl. naming conventions for processes, key figures, etc.) logical reporting model (multi-dimensional) source mapping providing a logical data access layer organizational processes for reporting and data quality assurance data integration of multiple sources (single version of truth) master data integration (catalogs) definition of ETL (extract, transform, load) and notification process time persistent and source/application independent data storage preserve historical structure changes OPTION: AUTOMATION high performing and flexible calculation engine for medium/large data volumes reporting: fast / interactive / ad-hoc front end independent base for efficient and flexible report building data quality assurance (validation, consistency, completeness/actuality, correctness) full automation of ETL, OLAP reprocessing and data quality assurance FRONT END APPLICATION(S) front end applications are accessing the logical reporting layer (DWH-SQL / OLAP-MDX) build pre-defined report packs; develop data mining models option: use mix of front end applications to cover all user needs (reader, explorer, analyst) 11

12 Processing Components prepare and create reports & analysis Usage Dashboard Reporting Analysis Front End ProClarity, Panorama, Business Objects, Cognos, Microstrategy, Microsoft Excel, etc. Presentation Business Intelligence Platform Extract Transform Load Data Warehouse* Web Services OLAP* Citrix / Terminal Services Data Mining Logical Reporting Model (according to reporting needs) Source Mapping (connect, transform source data) Reporting Web Services Source System Data Warehouse (DWH)* Data Integration Platform - source independent - persistent data - reflect structural changes - merge of multiple sources/catalogs - data quality enhancement - high performance data access (drill through, SQL reporting) - special transformations intra-group elimination, foreign exchange calculations, etc. OLAP CUBES* - pre-aggregated base for fast, interactive reporting & analysis - NOTE: can be used without DWH (!) 12

13 Core Concept Logical Reporting Model Organization (Dimension) management legal / retail Date (Dimension) Sales (Facts) Day Time (Dimension) Customer (Dimension) Product (Dimension) Multi-Dimensional Reporting Model The model is primarily derived from the union of all existing and future reporting and analysis requirements (content of rows, columns, cells and filtering) for all value chain related activities/ processes and extended by additional available source system information. Sales Channel (Dimension) amount, units Inventory (Facts) Source Mapping (connect, transform source data) Account (Dimension) Source System All primary context information of transactions with grouping character refers to a dimension, whereas each dimension may consist of one or more alternate hierarchies. Note: key figures and KPIs are usually a calculated member within a dimension hierarchy and not an indicator for a real dimension itself, whereas in an OLAP cube they may be consolidated in a shadow dimension. 13

14 Processing Components data storage areas DATA SOURCE DATA OLAP STORAGE SYSTEM WAREHOUSE CUBES ABBREV OLTP: Online Transaction Processing DWH: Data Warehouse; Data Integration Platform OLAP: Online Analytical Processing USAGE support of value chain processes/ activities add/modify/delete data collect, combine and store historical data of multiple sources/catalogs source independent pre-calculate and store all possible combinations of aggregates source independent OPTIMIZED for transaction processing and application usage not optimized for query for query of transactions and minor aggregates for storage of large data volumes (transactions) for query of aggregates space optimized for storage of aggregates of large data volumes (sparse matrix) ACCESS Proprietary; depends on storage system and application data model Standardized star-schema data model query language: SQL Standardized star-schema data model query language: MDX FRONT-END Proprietary application only. Query solutions are limited to proprietary data model (incl. third party products) Unlimited mix of reporting applications can be used: Microsoft Reporting Services, Brio, Microstrategy, Business Objects, etc. Unlimited mix of reporting applications can be used: ProClarity, MS-Office, Targit, Panorama, Cognos, Business Objects, Microstrategy, etc. 14

15 Business Intelligence Market (OLAP) facts & figures SOURCE: BI platform vendor selection criteria - open architecture, functionality, and pricing - minimize number of vendors/products involved - level of integration of all platform components - market share as indicator for ongoing platform development for number of service/solution providers 15

16 Reporting & Analysis platform / component recommendations Usage Dashboard Reporting Analysis Front End ProClarity (Microsoft), Microsoft Excel, optional: Microsoft Performance Point Server Presentation OLAP Web Services Citrix / Terminal Services Microsoft SQL Server 2005 Integrated BI Platform Integration Services SQL Server Analysis Services Logical Reporting Model Source Mapping Analysis Services Reporting Services Vendor Selection Criteria - market leaders involved - minimal number of vendors - full integration of all comp. - open architecture - full functionality covered - high number of srv. providers - good pricing Data Sources 16

17 Implementation Framework build of reporting & analysis platform ACTIVITIES PRE-REQUISITES BUILD USE REPORTING Report Specifications Data Quality Requirements Create Reports Create Dashboard Test & Deploy IT INFRASTRUCTURE Server (HW/SW) Network (Front-End Server) Front-End (Rollout) BI CONCEPT BI SETUP Logical Reporting Model (!) Master Data Management Source Mapping (!) Query / OLAP Model Data Quality Checks Optional Extension Data Warehouse ETL Process ORGANIZATION Metadata Repository KPI / Balanced Scorecard Reporting Processes Front-End Selection Training Usage / Support Data Quality Process PROJECT Project Organization Project Plan Core Platform Selection Project Management Communication Deployment Review 17

18 ibax partner for your business intelligence sustainable platform solutions instead of tool selling Our solutions create long-term economic value focusing high quality of products/development and services with cost and time efficient implementation and operation processes solid, extensible base, where platform grows with your company with business/result driven reporting & analysis profound expert knowledge for many years combined with internal best-practice methods/collection highly responsive services for operation and user support/maintenance With core skills in Architectural Concepts: Data Warehouse / OLAP, fully automated ETL and Notification Processes, Master Data Management Process: well structured project workflow (Evaluate - Envision - Empower - Excel) Technology/Platforms: SQL Server (T-SQL), Integration Services (SQL, MDX, VB/.NET), Analysis Services incl. Data Mining (MDX, DMX) and Reporting Services with ProClarity / MS-Office / Excel / Web Integration Specialties: Generic Solution Base; Automation, Database Performance & Tuning 21

19 Added Value for Reporting & Analysis starts with a solid overall platform solution and ends with a front-end implementation We deliver professional and sustainable business intelligence platforms to transfer your data to knowledge Find out more about our passion for your BI success michael.broennimann@ibax.ch Copyright ibax AG October 2006

20 COPYRIGHT All material in this presentation are copyright ibax AG and may not be used for any commercial purpose without ibax's prior consent in every specific case. The materials may not be altered without the prior consent of ibax AG. DISCLAIMER for this presentation The information and materials provided in this presentation are intended to be general and do not constitute advice in any specific case. Information provided does not create a legal relationship between ibax AG and the reader and ibax does not accept any responsibility or provide any guarantee of any kind with respect to the accuracy or relevance of information provided in this presentation. TRADEMARK The trademarks and logos of ibax and ER AnalytiX are registered trademarks of ibax AG. There is no right to use any trademark displayed in this presentation without the written permission of ibax AG or such third party that may own the trademarks. michael.broennimann@ibax.ch Copyright ibax AG October 2006