Agile for Data Teams: The Incremental Delivery Executive Guide
A practical, 17-page guide on how Agile for data teams actually works - why Scrum vs Kanban for data teams isn't a single choice, how to structure a data team backlog around real business value, and the data team metrics that replace sprint velocity as a measure of delivery performance. Built for CDOs, Heads of Data, and Analytics Directors, not another generic Agile primer.
Seven Parts, One Incremental Delivery Model
Every part of the guide corresponds to a full-length article on the Numlytics blog, so you can go deep on any single topic after reading the executive summary.
Why Data Projects Need a Different Agile Approach
The four conditions software Agile assumes and why data engineering only partially satisfies them.
Scrum vs Kanban for Data Teams
Where each framework fits, where each breaks, and the hybrid most mature data teams run.
Building a Data Team Backlog
RICE and WSJF adapted for data work, plus a reserved-capacity model that stops categories cannibalising each other.
Incremental Delivery: Bronze to Gold
Vertical slicing through the medallion architecture ship real value every sprint, not just after a big-bang build.
Data Team Metrics That Matter
A DORA-style framework built for data delivery frequency, incident rate, adoption, and time to detect.
The Data Sprint Retrospective
Four specific, recurring failure patterns to interrogate directly - instead of a generic "what went wrong."
Why Data Teams Miss Deadlines
Seven recurring, avoidable reasons with a named mitigation and a pre-sprint checklist for each.
Who This Guide Is For
Download the Executive Guide — Free
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