Context

Our data lived in over ten different places. Google Play, Apple App Store, Windows, Amazon, Samsung, Google Analytics, Google Ads, Apple Ads, Applovin. Each platform had its own interface, its own reporting logic, and its own definition of what a user was. Getting a complete picture of the business meant pulling from all of them manually, and only a few people knew how to do that well. Everyone else was working from a partial view.

What I did

I built a centralized data warehouse that pulled all of those sources into one place. I also created a data dictionary to make explicit what had previously only existed as tribal knowledge, specifically which values came from first-party sources and which came from third parties. The goal was to make cross-platform analysis something anyone on the team could do, not just the people who had been around long enough to know the quirks of each system.

Impact

The teams that used it got real value out of it. Cross-platform comparisons became faster and more reliable. But about half the team kept using their old tools. That was not a failure of the system. It was a signal that access alone does not change behavior. People have workflows, habits, and reasons to trust what they already know.