Data & Analytics
Data Governance
Who owns each dataset, what quality it must meet, how long it is kept and who may see it. Written down and enforced in the pipeline rather than in a policy document.
In short
Ownership, quality rules and retention.
What we deliver
- Data ownership and stewardship mapped
- Quality rules enforced in the pipeline, with alerting
- Retention and deletion schedules implemented, not just stated
- Access controls tied to roles
A good fit when
- An audit or certification is coming
- Nobody can say who owns a dataset
- Personal data is held with no deletion path
Technologies and methods
Chosen for each project, to fit your systems and your team.
- Policy
- dbt tests
- PostgreSQL
How we deliver
From first conversation to production.
Four stages on every engagement, scaled to the size of the project.
- 1
Understand
Clarify the users, goals, constraints, and current systems.
- 2
Plan
Map the main components, data, and integrations before implementation.
- 3
Build
Develop and review the work in small, testable increments.
- 4
Prepare
Plan deployment, operations, documentation, and ownership.
More in Data & Analytics
Prefer to talk it through?
A private consultation, 30 minutes with the founder, in your time zone.
Interested in Data Governance?
Tell us what you are working on. We start by understanding the problem, the people, and the systems involved.