Scrum vs Kanban for Data Teams
Neither framework is wrong for data work each fits a different slice of it. Where Scrum fits, where Kanban fits, and the hybrid most mature data teams run.
Build a Data Team Backlog That Delivers Value
Five work categories, no shared definition of value – the recipe for prioritising by whoever asked most recently. RICE, WSJF, reserved capacity, and triage for data teams.
Incremental Delivery: Bronze to Gold Fast
Building all Bronze then all Silver then all Gold is waterfall in Agile clothing. How to slice vertically and ship a real Gold output every sprint instead of waiting months.
The Metrics Every Head of Data Should Track
Sprint velocity measures estimation accuracy, not delivery performance. Four DORA equivalents for data teams, plus the quality and adoption signals velocity never surfaces.
What a Data Sprint Retrospective Should Cover
Generic retro questions produce generic answers. Four failure patterns every data retro should ask about directly and why checking last sprint’s action items matters most.
Why Data Teams Miss Deadlines & How to Fix It
Seven recurring deadline causes – schema changes, infra blocking, ad-hoc overload, big-bang delivery, lagging metrics, unaddressed retro patterns, staffing gaps and the fix for each.
Why Data Projects Need a Different Agile Approach
Software Agile breaks on data work. Six structural friction points – scope ambiguity, infrastructure dependencies, delayed quality failures and four adaptations that actually work.
Incremental Delivery for Data & Analytics Teams
Pillar guide to a seven-part series: why Agile fits data differently, how Bronze–Silver–Gold becomes your sprint increment, and the metrics that reveal whether delivery is working.