Databricks governance as code
One folder of reviewed files decides who can reach which data, with which role, in every environment. Plus cost per team, AI spend, and daily checks on your data, pipelines and security.
For data platform teams who manage Databricks access by hand.
Can your Databricks team answer these today?
Access is granted by hand, one workspace at a time
“I need workspace and data access.”
Who approved that? Nobody knows.
Every request means clicks in each workspace, and one gets forgotten.
Old access stays, and nobody can show who approved it.
New colleagues wait for access before they can start.
The workspaces drift apart, and nobody can say why a grant exists.
One folder of files decides who gets what
Groups from your identity provider, such as Microsoft Entra ID or Okta, become clear roles per team: engineers, analysts and business users. Each role sets two things: what the group can do in Databricks, and which data it can read or change. A person who joins the group gets that access in development, acceptance and production at once. A person who leaves the group loses it. This works the same on Azure, AWS and Google Cloud.
1team: analytics 2engineers: read, write
Six areas, one folder of files
Groups from your identity provider become team roles. Each role sets what a group can do in Databricks: use the workspace, use Databricks SQL, or only view what others publish.
Each group gets exactly the data rights its files describe in Unity Catalog: read, write or create, per catalog and schema.
Each catalog opens only in the workspaces you allow. Production stays separate.
Catalogs and volumes live on your own cloud storage.
SQL warehouses and compute policies per team, each with a monthly budget.
Cost, pipelines and security, watched every day.
Watched every day, the same in every environment
A daily dashboard shows what each team spends, against its monthly budget.
One dashboard shows the status of every job and pipeline, and the size and last update of every table. A failed run is caught and fixed.
Every workspace is checked against Databricks best practices, in dev, acc and prd.
See what your LLM use costs, per model, before the bill arrives.
All of this comes with governance, also on the Databricks you run today.
Request a custom demoChange a file. Review it. Merge it.
A team member changes one line, in your own repository.
A colleague approves the change. The history shows who changed what, when, and who approved it: the trail an auditor asks for.
Every environment follows. Only what changed gets written.
New colleague? Add them to the group, and access follows. Remove a file, and the data stays.
Every team gains
On the Databricks you run today, or built into a platform we run for you
Governance as code is part of the foundation, which RevoData builds and runs in your own cloud.
Run it yourself, or let our service desk run it for you, with an SLA.
Frequently asked
Does it copy our users and groups?
No. Databricks syncs the groups from your identity provider, such as Microsoft Entra ID or Okta. Governance as code turns those groups into roles and access.
How does someone lose access?
Remove them from the group in your identity provider. Their access ends in every environment.
Is there an approval portal?
No. A colleague approves each change in your own repository, like any code review.
Does it build our workspaces?
No. It works on the Databricks workspaces you have today, whether RevoData runs them or you do.
What if a file is removed by mistake?
The data stays. Governance as code never deletes data because a file was removed.
Access defined once, reviewed like code
See how your groups become roles, and how one reviewed change reaches every environment.
Request a custom demoDatabricks Gold Partner · ISO/IEC 27001 and NEN 7510 certified · DORA-compliant implementation at a regulated financial client