---
title: "Who decides what this column means?"
slug: "ownership-register"
type: recipe
locale: en-US
canonical: "https://www.coremodels.io/recipe/dbt/ownership-register"
updatedAt: "2026-09-24T22:02:28+03:00"
---

# Who decides what this column means?

41% of analytics teams say data ownership is ambiguous. dbt can tell you who owns a model. Nobody owns a definition.

dbt's own 2026 State of Analytics Engineering put ambiguous data ownership among the top pains teams report, alongside trust and quality — and it is the one with the least tooling. dbt groups and model owners tell you who maintains the SQL. They do not tell you who decides what `customer_status` is allowed to contain, who to ask before adding a value, or who should have been consulted when someone changed it last quarter. So the answer is usually 'ask in #analytics and see who replies'. This workspace makes ownership a property of the meaning rather than of the file: every column and every vocabulary can carry an owner, a steward team and a review cadence, sitting as columns in a grid you can sort and filter. The most useful view is the one that shows what has no owner at all — that list is your actual to-do, and it is the prerequisite for every review, notification and escalation workflow you might build later.

## What you do

1. Every column and vocabulary gains an owner, a steward team, a review cadence and a decision forum.
2. Filter to 'no owner'. That list is the real work.
3. Start with the vocabularies — that is where the arguments live.

## Articles

- [Ask in #analytics and See Who Replies](https://www.coremodels.io/connector/dbt/h7-ownership)
- [Building an Ownership Register That Survives Contact With a Real Team](https://www.coremodels.io/connector/dbt/t8-ownership)