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Deploying Business Intelligence

Deploying Business Intelligence. Competitive/Business Intelligence Systems. Transforming disparate data into information that is accessible, timely, meaningful, & actionable BI is synonymous with past applications: Decision Support Systems (DSS) Executive Information Systems (EIS)

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Deploying Business Intelligence

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  1. Deploying Business Intelligence Competitive/Business Intelligence Systems

  2. Transforming disparate data into information that is accessible, timely, meaningful, & actionable BI is synonymous with past applications: Decision Support Systems (DSS) Executive Information Systems (EIS) Multidimensional modeling (E.F. Codd circa 1990s) What is BI?

  3. BI is an Iterative Process

  4. What Questions can BI answer? • Where are we? • What were our sales this month? • Where are we going? • Are our sales trending up or down? • Why is this happening? • Why are sales going down? • What is going to happen in the future? • Forecasting / What If analysis • How can I plan for the future? • Planning / Goal Setting

  5. Operations ERP Reporting/Analysis KPI tracking Maximizing profits Risk Management Activity Based Costing Logistics Customer Relationships Sales forecasting Segmentation Cross-selling CRM analysis Campaign planning Customer profitability Where is BI utilized?

  6. Major BI/OLAP Vendors • Oracle OLAP • SAP BW • MS-SQL Server & Analysis Services • Hyperion Essbase/IBM • Microstrategy • Business Objects • IBM-COGNOS

  7. Current State of BI Industry • Microsoft has entered the market • ERP vendors are offering BI tools • Web deployment is CSF for all BI vendors However, • Successful BI deployment requires collaboration between IT & business users • Most BI deployment problems revolve around people & process issues – not tool selected

  8. BI Design Considerations • Project Scope (phased approaches typically fare better than massive scale) • Buy-in must exist on the part of IT & business • Design must be focused on needs of business users • User expectations must be managed

  9. BI Design Considerations (cont.) • Source data • Does access to data exist? • How many sources/what platform types of data exist? • Does BI initiative include DW? • What data definition issues exist? • What data cleansing / transformation issues exist? • Who is responsible for cleansing / transforming data to useable state?

  10. BI Design Considerations (cont.) Reporting vs. Analysis Needs • Entirely different functions • Each involves different user audience • Each requires different BI tool • Each requires different source data • Each requires different design approach

  11. BI Design Considerations (cont.) OLAP / Multidimensional Cubes • How many to build? • What should be included in each? (breadth & depth) • Who will receive? • What security levels should exist? • What are cube update considerations? (when, how frequent, time length of update) • What are end-user performance issues? • What is process for modifying / augmenting cubes?

  12. BI Design Considerations (cont.) Other OLAP Considerations • What dimensions? How many? • What time dimensions? • What levels in hierarchies? • What measures? How many? • What pre-built calculations and/or summaries should be created?

  13. The Business Case for BI Above all else, BI must have a strong business case to succeed. Business Case must show that: • BI can deliver high business value to involved stakeholders • Benefit of BI can cross functional boundaries • Benefit of BI can cross organizational boundaries • BI can offer measurable short term ROI, as well as long-term ROI

  14. The End.

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