Data Modeling & Governance
So that every metric means the same thing, every time — and everyone knows why.
We turn raw data into documented, trustworthy business models. Core entities like customers, accounts, subscriptions and orders get defined relationships, grains and lifecycle states, so a metric means one thing across every report.
How we work
- 01
Find the disagreements
We start by asking three teams to define 'active customer' and writing down the three different answers. That list is the real scope of the work.
- 02
Define entities and grains
Each core entity gets one definition, one grain, and explicit lifecycle states — so 'churned' has a date, a rule, and no ambiguity.
- 03
Build the metric layer
Metrics are defined once, in code, and consumed everywhere. A dashboard, an export and an agent all resolve the same definition.
- 04
Enforce it
Tests and CI checks mean a change to a definition is a reviewed decision rather than something discovered a quarter later.
What changes
- Meetings stop opening with an argument about whose number is right
- New reports reuse definitions rather than reinventing them
- A governed foundation that AI agents can query without hallucinating