Data governance is the system of policies, roles, and controls that ensures your data is accurate, secure, discoverable, and compliant. We build governance frameworks that make your data trustworthy without slowing your teams down.
Governance is not paperwork. It is the difference between numbers your leadership can defend and numbers nobody can explain when a regulator, auditor, or board member asks.
Two dashboards disagree and nobody knows which is right. A spreadsheet with customer data circulates by email. An ex-employee's account still has warehouse access. A GDPR deletion request turns into a week of manual archaeology.
None of these are exotic failures. They are the default state of any data platform that grew faster than its controls, and every one of them is preventable with the same set of foundations.
Each pillar is implemented in your actual platform, not in a policy PDF. Controls that live only in documents do not control anything.
Every dataset tagged by sensitivity level: public, internal, confidential, restricted. Classification drives access control and determines handling requirements automatically.
Role-based and attribute-based access policies. Column-level security, row-level filtering, and dynamic data masking so users only see what they are authorized to see.
Trace every record from source to destination. Know where a number came from, what transformations were applied, and when it was last updated. Essential for debugging and audits.
Automated checks for freshness, completeness, uniqueness, and referential integrity. Alerts fire before bad data reaches your dashboards or models.
Retention policies, GDPR and CCPA data handling, right-to-delete automation, and audit trails. Built to satisfy regulators, not just check a box.
A searchable inventory of every dataset, table, and field in your organization. Business definitions, owners, freshness indicators, and usage metrics in one place.
We ground governance work in the frameworks that actually apply to your operation, so the controls we build map to obligations you can point at.
| Framework | What it demands of your data | How we implement it |
|---|---|---|
| GDPR | Lawful basis, minimization, right to access and deletion, breach readiness for EU personal data | Field-level classification of personal data, masking by default, automated subject request workflows, retention enforcement |
| EU AI Act | Risk-tiered obligations for AI systems, data quality and documentation duties for training and operation | Documented data provenance for AI workloads, quality gates on model inputs, human oversight points designed into workflows |
| CCPA / CPRA | Disclosure, deletion, and opt-out rights for California consumers | The same classification and deletion machinery as GDPR, extended with consumer request handling |
| SOC 2 alignment | Demonstrable access control, change management, and monitoring | Least-privilege IAM, audit logging, and reviewable access processes that make evidence collection routine |
Catalog what data exists, where it lives, who touches it, and how sensitive it is. You cannot govern what you have not mapped.
Implement least-privilege roles, masking, and audit logging in the platform itself. The riskiest gaps close first.
Freshness, completeness, and integrity checks wired into pipelines, with alerting and clear ownership per dataset.
Catalog, documentation, review cadence, and training so governance keeps working after we hand it off.
Good governance is invisible on a normal day and invaluable on a bad one: the audit, the breach scare, the deletion request, the disputed number.
Check every statement that is true right now. Honest answers give a useful verdict.
Done right, it speeds them up: a catalog ends the hunt for the right table, trusted definitions end metric arguments, and pre-approved access patterns end ticket queues. Friction comes from bad governance, not governance.
You need the proportionate version: classification, least-privilege access, and basic quality checks take days to establish and prevent the failures that are expensive at any size.
Yes, that is the most common shape of the work. We inventory what exists, close the riskiest gaps first, and phase in the rest without freezing your roadmap.
Named owners inside your organization, equipped with documentation, review cadences, and training. We design for handoff, with optional retainer support.
Tell us what data you hold and what keeps you up at night. We will map the gaps and phase the fixes.