![Table of Content ,[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommandé
Recommandé
Contenu connexe
Tendances
Tendances (20)
En vedette
En vedette (9)
Similaire à Business Intelligence Challenges 2009
Similaire à Business Intelligence Challenges 2009 (20)
Dernier
Dernier (20)
Business Intelligence Challenges 2009
- 1. Current Business Intelligence Challenges By Lonnell Branch
- 4. Where Is Business Intelligence Headed?
- 6. Business Intelligence Architecture Reporting tools Report Servers ETL Servers Database Servers Facts Dimensions Aggregates
- 7. Query Tool Diversity Let’s Start Reporting
- 8. Query Overload Why can’t I query all markets for 18 months of product sales by store, demo and sales campaign ?
- 9. Query performance tune up kit How do we get faster queries? Bigger Servers? More Servers? Faster Servers? More Indexes? Composite Indexes? Bitmap Indexes? More Partitions?
- 10. Has the ETL Run Yet? How do we coordinate ETL and Reporting Processes?
- 11. What is in the data warehouse? Business users want to know. Power users need to know. Do we really know?
- 13. How do we get BI to the small guy?
- 14. What is the BI Portal? Is the BI portal the most productive environment for end users, developers or clients?
- 15. What Business Reports are availabe from the BI tool?
- 16. How do we improve business performance with BI? BI Architects? Data Architects? Report User’s Input?
- 17. What do users Want?
- 18. Less Complexity
- 19. Data Democracy
- 20. Speed !!!
- 21. Future State
- 24. Suggestions
- 26. Analytically improve the rules Use: Find the relationships between customers Example : Sort customers into groups with different buying profiles. Operation : Analysis is generally done offline, but the results can be used in automated decisions – such as offering a given product to a specific customer Descriptive analytics can be used to categorise customers into different categories – which can be useful in setting strategies and targeting treatment.
- 27. Add predictive insight Use: Identify the odds that a customer will take a specified action Example : Will the customer respond to this promotion? Operation : Models are called by a business rules engine to “score” an individual or contact. Predictive analytics often rank-order individuals. For example, credit scores rank-order borrowers by their credit risk – the higher the score, the more “good” borrowers for every “bad” one.
- 28. Let’s Plan for Change
- 29. Lets Develop A BI Strategy Business Performance Management Tactical Analysis Operations Monitoring Business Goals Information BI Infrastructure Business Strategy Analytic Capabilities Intelligence People
- 31. The End