Agile Data Warehousing/Business Intelligence: Addressing the Hard Problems
summary
Recommends adopting Data Vault 2 for scalable DW architecture, adding CI/CD, automated testing and a catalog of ~65 database refactorings to fix data technical debt. Argues for question stories and vertical slices so some releases can be hours while complex analyses often need six to eight weeks; shift from Scrum projects to Kanban/continuous delivery, shorten sprints to one week, and evolve schemas safely (rename column by adding new column + trigger + deprecation window) so production changes don’t break integrations.
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chapters (12)
- 0:00Intro
- 2:24Agile Data Ways of Thinking (WoT)
- 10:37Key Model: Data Source Diagram
- 11:29Key Model: Conceptual Diagram
- 18:48Embrace Evolution
- 22:12Agile Data Roles
- 23:07Generalizing Specialists
- 27:46Evolve via Lean Continuous Delivery
- 31:36Look-Ahead Data Analysis: Agile
- 34:22Look-Ahead Data Analysis: Continuous Delivery
- 36:25Active Stakeholder Participation
- 39:24Database Refactoring
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