Data & Intelligence service
Data Governance
Make data responsibility practical through named stewardship, usable policy, visible lineage, quality accountability, and controlled access across its lifecycle.
Service context
Data governance becomes useful when it changes how data is created, accessed, interpreted, and retired. We focus on the critical domains and decisions where unclear responsibility creates real operational or regulatory risk.
Policies are translated into ownership, workflow, metadata, quality controls, and evidence inside delivery tools rather than left as a separate document that teams must interpret alone.
Problems addressed
- 01
Policies exist, but teams cannot identify who can approve access, resolve a definition, or accept a quality exception.
- 02
Sensitive and critical data is not consistently classified, traced, retained, or connected to its downstream use.
- 03
Governance programs attempt broad coverage before proving a workable stewardship model in the domains that matter most.
Engagement approach
Prioritize data domains by business use, sensitivity, operational dependence, and current accountability gaps.
Define stewardship roles, classification, access, quality, metadata, and lifecycle workflows with decision rights that teams can follow.
Embed governance checks and evidence into data delivery, then expand from measured domain adoption and unresolved risk.
Delivery stages
- 01
Prioritize
Rank domains by business use, sensitivity, operational dependence, and accountability gaps.
- 02
Assign
Define owners, stewards, decision rights, classifications, and escalation paths.
- 03
Embed
Integrate access, quality, metadata, lineage, retention, and exception workflows.
- 04
Expand
Measure adoption, unresolved risk, decision time, and domain readiness before scaling.
Technology context
Microsoft Purview
Collibra
dbt
PostgreSQL
Value direction
These are intended operating improvements, not guaranteed results.
- Named decision rights for access, definitions, quality exceptions, and lifecycle changes.
- Better visibility into sensitive and critical data, its lineage, and the workflows that depend on it.
- Policies translated into repeatable delivery and operating practices.
- A governance roadmap based on domain adoption and risk evidence rather than document completion.
Decision questions
Delivery accountability
Make responsibility visible across the service lifecycle.
Delivery services connect role clarity, operating ownership, quality expectations, and escalation paths to the same system context.
Start a conversation