Collibra Data Products User Group — June 2026 Session
Summary: Alexandra Jorgenson shared a summary of the first Data Products User Group session, covering the journey of data products from inception to scaling and proving ROI. Key takeaways included the importance of defining data products with ownership and context, carefully selecting initial use cases, establishing foundational elements, and using a gradual scaling approach. Feedback from attendees highlighted organizational buy-in and alignment as major challenges. Future sessions will explore topics like data contracts and change management.
Thanks to everyone who joined our first Data Products User Group session! Here's a quick summary to share alongside the recording and slides.
Watch the recording here
Download the slides here
What we covered
We walked through three phases of the data products journey — getting started, scaling, and proving ROI — with practical frameworks and live poll responses from attendees shaping the conversation in real time.
Key takeaways
Define before you build. A data product isn't just a table or dashboard. It needs a named owner, business context, quality rules, SLAs, and discoverability. Every data product = data + context + controls + access.
Pick your first use case carefully. Look for recurring pain, existing demand, data you already have, bounded scope, a committed owner, and a win you can show off. Use a value vs. effort grid to prioritize.
Nail the five foundations early. Named ownership, a governance baseline, shared semantics, a reusable template, and a central marketplace. Get these right once and every product after gets easier.
Scale through a flywheel, not a big bang. Pilot → codify → expand → reuse. Launching a full marketplace before you have a proven first product is the most common way to overspend.
Tie every product to a value driver. Revenue, cost, risk, or speed. If you can't connect a data product to at least one of these, pause before building.
Track adoption weekly, report ROI quarterly. Leading indicators: active consumers, time to first data, reuse rate. Lagging indicators: hours saved, cost avoided, revenue influenced.
What you told us
The biggest bottlenecks in the room: organizational buy-in and change management, defining ownership, and getting producers and consumers aligned.
What's next
Upcoming topics will dig deeper into data contracts, change management, ownership models, and measuring ROI. Have a topic you want covered? Post it in the Data Products User Group in the Collibra Community.
Chet Stagnaro
·2 months agoThanks for sharing the materials and the key takeaways for planning and governance.