Free Data Governance Checklist: 25-Point Maturity Self-Assessment

1. An executive sponsor is accountable for data governance. 2. Critical data domains (e.g., customer/patient, finance, product) each have a named data owner. 3. Data stewards are identified and have time allocated to the role. 4. A governance council or working group meets on a regular cadence. 5. Decision rights for data definitions and issues are documented (RACI).

Definitions & Metadata

6. Top KPIs have one documented, agreed definition. 7. A business glossary exists and is easy to find. 8. Critical data elements are identified and documented. 9. Data lineage for key reports is understood from source to dashboard. 10. A data catalog or inventory shows what data exists and where.

Data Quality

11. Data quality dimensions (accuracy, completeness, timeliness, etc.) are defined. 12. Quality rules are measured for critical data elements. 13. A data quality scorecard is reviewed by leadership. 14. There is a clear process to report and resolve data issues. 15. Root causes are fixed at the source, not just patched in reports.

Access, Privacy & Security

16. Sensitive data (PII, PHI, financial) is classified and labeled. 17. Access follows least-privilege and is reviewed periodically. 18. Data retention and disposal rules are defined and followed. 19. Data sharing with vendors and partners is governed by agreements. 20. Regulatory requirements (e.g., HIPAA, state privacy laws) are mapped to controls.

Culture & Value

21. Governance goals are tied to business outcomes and KPIs. 22. Policies are written in plain language and published. 23. Staff receive data literacy or stewardship training. 24. Governance metrics are tracked and reported. 25. AI and analytics initiatives follow governance standards.

The 25-Point Data Governance Checklist

Ownership & Accountability

Definitions & Metadata

Data Quality

Access, Privacy & Security

Culture & Value

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