Map ownership
Every table and pipeline in scope assigned an owner and a steward, with descriptions and tags so people can find what they need.
4.9 / 5Databricks data governance that people actually follow.
Databricks data governance for the customer, website and marketing data in your lakehouse: clear owners, sensible access and visible quality.
Selected work, in motion.
The digital experiences that connect to a wider business system.Nobody owns the table.
Governance problems show up as questions nobody can answer. Who owns this? Who can see it? Can we trust it?
BeforeAfter
Tables with no owner and no descriptionEvery table owned, described and tagged in Unity Catalog
Everyone can see everythingAccess granted by role, with personal data masked
Quality problems reported by the finance teamQuality monitoring that alerts the owner first
No idea what breaks if a table changesLineage showing every upstream source and downstream report
What's included
Clear owners. Clear rules.
We govern the customer and marketing data flowing from your web and product stack. Enterprise-wide programmes belong with a specialist Databricks consultancy.
Define access rules
Unity Catalog grants by group and role, with row filters and column masks on personal data such as emails and addresses.
Monitor quality
Freshness, volume and schema checks on key tables, alerting the table owner when something drifts from normal.
Trace the lineage
Unity Catalog lineage checked for the tables in scope, so you can see what breaks before changing a column or a source.
Security, by consideration.
Trust is part of the build.
For your Databricks project, we consider data sources, workspace permissions, pipelines and downstream consumers as part of one connected build.
See our approachConnected systems. Considered safeguards.
Changes you can trace.
GitHub workflows, peer review and dependency checks bring decisions into the release process.
Protected in transit.
Certificate configuration, HTTPS and secure headers help protect the path between your users and your systems.
Intelligence with limits.
Scoped tool access, validated inputs and human approval where automated actions carry consequences.
Scope, set, monitor.
We start with the data that carries the most risk: personal and revenue data.
- 01
Audit
Tables, owners, access and personal data in scope listed, with risks ranked.
- Data inventory
- Access audit
- Risk list
- 02
Set the rules
Owners assigned, then grants, masks and tags applied in Unity Catalog.
- Ownership register
- Access policies
- Tagging scheme
- 03
Monitor
Quality monitors and access reviews set on a schedule your team can keep.
- Quality monitors
- Review calendar
- Governance guide
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Built to driveMore product discovery.
Trusted across our practice
Working together. In their words.
Independent reviews. Long-term working relationships.
“We’ve been working with Stega & Gabriel for the last two years. Cannot recommend them enough. They’re responsive, professional & an asset.”
“After a website (re)launch, they are also always accessible and happy to help. I highly recommend everyone who is looking for a new and more stable website in Webflow, to work with Stega!”
“Stega Creative team not only understood our needs and vision for the websites, but they also came up with improvements.”
Databricks governance questions.
A few things worth discussing before your Databricks data governance takes shape.
What does Unity Catalog do in Databricks?
Unity Catalog is the governance layer in Databricks that manages access, lineage, discovery and auditing for data and AI assets across workspaces. Permissions are set once and apply everywhere. We use Unity Catalog to assign owners, restrict personal data with masks and filters, and trace how tables feed reports.
How do you protect personal data in Databricks?
Personal data in Databricks is protected with Unity Catalog column masks, row filters and group-based grants. We tag columns holding emails, names or addresses, mask them for everyone who does not need them and keep an audit trail of who queried what. Retention decisions stay with your team.
Does Databricks data governance help with GDPR?
Databricks data governance helps with GDPR by showing where personal data lives, who can access it and how it flows. Unity Catalog tags, lineage and audit logs make access and deletion requests traceable. Compliance still depends on your policies and legal advice, which we support but do not replace.
How long does a Databricks governance setup take?
The audit needs the most care. Applying grants, masks and tags in Unity Catalog is quicker once owners and rules are agreed.
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