Data governance for companies that grew faster than their data stack

Companies usually notice their data governance problem the same way: two departments present conflicting numbers in the same meeting, and nobody can say confidently which one is right.

The instinct is to buy a data catalog and call the problem solved. That's rarely what's missing. What's missing is ownership — a named person or team accountable for each core dataset's definition and quality, documented somewhere everyone can find it.

Beyond ownership, three controls cover most of the risk that actually causes incidents: access controls tied to role rather than individual request, a single source of truth for each core metric (revenue, headcount, inventory) with everything else required to derive from it, and change logging on schema updates so a silent field rename doesn't break five downstream dashboards.

None of this requires a platform migration. It requires deciding, in writing, who owns what — and then building the pipelines and dashboards you already have around that decision instead of around whichever team built them first.