Rapid Recall 39–76

1. Why is logical taxonomy/model useful for mapping?
2. Remediation vs transformation?
3. Optimistic vs pessimistic loading?
4. What factors shape the population approach?
5. What does CDC contribute to population?
6. Why group BI users?
7. Tactical BI vs Strategic BI?
8. Self-service BI vs unmanaged analytics?
9. What is operational analytics?
10. What is OLAP for?
11. Why is a release plan necessary?
12. Release vs iteration?
13. Pilot/sandbox vs production?
14. What should load monitoring look for?
15. Why tune BI based on usage?
16. Why expose delivery status transparently?
17. What does the data dictionary/glossary do?
18. Lineage vs impact analysis?
19. Why keep logical and physical models synchronized?
20. What should integration tools support besides transformation?
21. Name major BI tool/capability families.
22. Why prototype?
23. Why make audit data queryable?
24. What belongs in readiness assessment?
25. Why build a release roadmap?
26. What does configuration management protect?
27. Name five business/change readiness factors.
28. What does DW governance do?
29. What does business acceptance require?
30. What belongs in UAT?
31. Name the four trust-supporting architectural components emphasized around Section 6.1.
32. What do SLAs specify?
33. What belongs in reporting strategy?
34. What can a Center of Excellence support?
35. What do usage metrics measure?
36. What do subject-area coverage metrics measure?
37. What do response/performance metrics measure?
38. What is the final Chapter 11 mental model?

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