Start from the decision
Before modeling a single table we ask which decisions this data should inform and who makes them. That question prunes the firehose of possible events down to the ones that matter and defines what 'correct' even means.
A tracking plan, agreed up front, keeps event names and properties consistent across web, mobile, and backend. Without it, every analysis begins with a week of reconciling what 'signup' meant in three different places.
Model once, trust everywhere
We transform raw events into a small set of clean, documented models that become the single source of truth. Metrics get defined once, so finance, product, and marketing stop arguing about whose number is right.
Tests run on the data itself — freshness, uniqueness, and referential checks — so a broken upstream change is caught before it reaches a chart someone is about to present to the board.
Make it boring to use
The best outcome is unglamorous: a handful of dashboards people trust, a metrics layer that answers ad-hoc questions, and clean tables ready for the next ML or AI use case.
Adoption is the only metric that matters here. Analytics that change decisions are worth ten that merely exist.