Bill Hostmann Tutorial: Data Warehouse: Selecting the BI and ETL Products That Are Right for You! These materials can be reproduced only with Gartner’s official approval. Such approvals may be requested via --

Key Issues 1. What significant advancements and trends are occurring in data integration tools for building data warehouses and BI applications? 2. What are the key criteria to consider when evaluating data integration technologies? 3. What significant advancements and trends are occurring in BI tools? 4. What are the key criteria to consider when selecting BI tools and technologies? Copyright © 2002

Majority of construction effort Construct 1. Definition 2. Data Identification and Inventory 3. Tool Evaluation/ Selection 4. Develop, Implement, Train Consume 5. Discovery and Exploration 7. Develop Decision Alternatives 6. Access, Monitor, Analyze Facts 8. Share and Collaborate 9. Effect Change A Successful BI Project Is Based on a Well-Defined Methodology Copyright © 2002

A BI Solution Must Integrate and Align to Deliver Maximum Business Value Data Integration Data Integration BI Tools BI Applications BI Applications Metadata Security Data Sources Data Warehouse Management/Administration Business Users Value Intranet/Extranet Copyright © 2002

Data Re-Engineering Contact Efficiency Data Analysis Relationship Identification Copyright © 2002 Categories of Data Quality Technology

Tools to Improve Data Quality As of 08/02 Ascential Software Avellino DataFlux/SAS Evoke Software Firstlogic Group 1 Software Innovative Systems Trillium Software Data Analysis Relationship Identification Generic Data Re-Engineering Contact Efficiency = Strong= Moderate (Blank) = No Functionality= Weak Sample Vendor List Copyright © 2002

ETL ROI ‘Levers’ How Do You Estimate Your ROI? Number of data sources Type of data sources Complexity of transformation Complexity of integration Resources Skills Metadata requirements Intertool integration requirements Environment stability Data quality requirements Data volumes Time boundaries Copyright © 2002

Data Integration: Selecting the Best Tool for the Job Integration BrokersETL Tools Adapters Transformation Business Process Mgmt. Management Services Intelligent Routing Message Warehouse Metadata Repository Transport Mechanisms Development Language Real-Time Integration Bulk Data Movement StrongWeak Copyright © 2002

ETL Magic Quadrant Ability to Execute Completeness of Vision Visionaries Niche Players Challengers Leaders Evolutionary Technologies International iWay Software Ascential Software Microsoft Computer Associates DataMirror SAS Oracle Data Junction IBM Sagent Acta Technology As of May 2002 Informatica Hummingbird Cognos Ab Initio Software Embarcadero Technologies From “ETL Magic Quadrant Update: A Market in Evolution,” May 2002.

What happened? Why did it happen? What will happen? Scheduled Interactive Event Reporting Ad Hoc Query OLAP Data Mining Advanced Analysis and Forecasting BAM CPM Most Common BI Needs Copyright © 2002 Large Enterprises Typically Need Multiple BI Tools

Copyright © 2002 Consider the Needs of Multiple Types of Users

User Functionality and Flexibility Required Training Investment and Cost High Low Parameter-Driven Reports – 30% Ad Hoc Query – 10% Static (Published) Reporting, Including OLAP Viewing – 60% Copyright © 2002 BI Functionally — Selecting the Right Mix

Copyright © 2002 Enterprise BI Suites and Reporting Magic Quadrant Completeness of Vision Ability to Execute Business Objects Cognos Oracle Computer Associates InfoBuilders MicroStrategy Challengers Leaders Visionaries Niche Players Hummingbird As of August 2002 Microsoft Crystal Decisions Actuate Brio Software March 2002 August 2002 From “Business Intelligence Magic Quadrants: Turbulent Waters,” August 2002.

Convergence: Enterprise BI Suites and Robust Reporting Technologies Highly Interactive OLAP Viewing Ad Hoc Query Batch-Oriented Sophisticated Formatting Highly Scalable High Performance High Usability Semantic Layer Crystal Information Builders Actuate Cognos Business Objects Brio 1 Brio 2 Microstrategy Oracle 1 Oracle 2 “New EBIS” User- Centric Microsoft Hummingbird Q403 Estimate Q302 Publishing/ Distribution Enterprise BI Suites Robust Reporting Oracle 1 — Oracle Discoverer Oracle 2 — Oracle Reports Brio 1 — Brio Intelligence Brio 2 — Brio Reports Convergence EBIS Attributes Robust Reporting Attributes Multiple Output Types Copyright © 2002

BI Platforms Magic Quadrant Copyright © 2002 Completeness of Vision Visionaries Niche Players Challengers Leaders Ability to Execute As of August 2002 AlphaBlox Arcplan Hyperion Microsoft Oracle Sagent SAS Crystal Decisions SAP Microstrategy WhiteLight Systems PeopleSoft Computer Associates ProClarity March 2002 August 20/02 Spotfire From “Business Intelligence Magic Quadrants: Turbulent Waters,” August 2002.

Visibility Technology Trigger Trough of Disillusionment Peak of Inflated Expectations Plateau of Productivity Slope of Enlightenment Collaborative BI BAM BI Web Services XML Enablement Mobile and Wireless BI BI/aCRM ERP/BI BI Portals Data Mining as part of BI OLAP Production/ Formatted/ Web Reporting Financial BI Applications EBIS BI Platforms At risk Moving forward Thin Client Alerting B2B BI Extranets B2C BI Extranets CPM No movement BI Hype Cycle as of September 2002 Copyright © 2002 BI Technology Trends — Emerging Pattern Towards BI Networks

Wireless Web Services Real Time BI Portals Build an Objective Evaluation Criteria Checklist Integration with Infrastructure Functionality Reliability Scalability Vendor Viability Pricing Customer References Support/Services Documentation Partners Scrutinize hype Copyright © 2002

Rating “We’d like to have you as a client. We offer you a 50 percent discount on a $1.5 million site license. Please decide now.” “We sell solutions …” “We will be your strategic partner; we’ll do everything for $450,000.” “We have great stuff, but not everything. This is how it fits in your overall framework. We also have some partnerships for things we don’t do” – – + +/–+/– Copyright © 2002 Intangible Factors Can Make or Break Tool Selection

Recommendations Before you evaluate tools and vendors, define your objectives, requirements, architecture and vision. View data quality as a strategic business issue rather than just an IT problem. As “data integration” markets continue to converge, heavily weigh strategic partnerships in your ETL evaluations. Minimize BI tool proliferation, but recognize that today a single tool may not meet all your needs. Overlook vendor hype; focus on objective criteria based on user requirements and business value. Copyright © 2002