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.
