Agile applied to data warehousing
Collier adapts iterative, incremental delivery and test-driven practices to business intelligence projects. BI is built in small production-ready increments rather than long waterfall cycles.
Agile analytics
3 ideas
Value-driven prioritization
Features are sequenced by the business value they deliver so stakeholders see working results early. Frequent delivery of usable analytics de-risks large data programs.
Automation and testing enable agility in data
Continuous integration, automated testing, and repeatable builds make iterative data work sustainable. Engineering discipline, not just process, is what makes agile analytics feasible.