Data Governance Framework
Assess, score, and remediate your organization's data governance posture across 6 domains.
What This Covers
- Data Quality — Completeness, accuracy, consistency, timeliness scoring
- Data Cataloging — Asset inventory, lineage tracking, metadata management
- Access Control — Role-based permissions, least privilege, data classification (public/internal/confidential/restricted)
- Compliance Mapping — GDPR, CCPA, SOX, HIPAA, PCI-DSS, industry-specific regulations
- Retention & Lifecycle — Retention policies, archival schedules, deletion procedures, legal hold
- AI/Agent Data Governance — Training data provenance, model input/output logging, bias detection, PII handling in agent workflows
How to Use
When asked to assess data governance:
- Ask which domains are priority (or assess all 6)
- For each domain, evaluate 8 controls on a 0-3 scale:
- 0 = Not implemented - 1 = Ad hoc / informal - 2 = Documented and partially enforced - 3 = Automated and continuously monitored
- Calculate domain score (sum / 24 × 100)
- Calculate overall governance score (average of domains)
- Generate remediation roadmap prioritized by risk
Scoring Interpretation
| Score | Rating | Action |
|---|---|---|
| 0-25% | Critical | Immediate remediation — regulatory risk |
| 26-50% | Developing | 90-day improvement plan required |
| 51-75% | Managed | Optimize and automate weak areas |
| 76-100% | Optimized | Maintain and benchmark against peers |
Domain 1: Data Quality Controls
- Data profiling automation (duplicate detection, format validation)
- Quality dashboards with SLA thresholds
- Root cause analysis for quality failures
- Stewardship program (assigned data owners per domain)
- Quality gates in data pipelines (reject bad data at ingestion)
- Business rule validation (domain-specific logic checks)
- Cross-system reconciliation (source vs target matching)
- Quality trend tracking (month-over-month improvement metrics)
Domain 2: Data Cataloging Controls
- Automated asset discovery (databases, APIs, files, SaaS)
- Business glossary with agreed definitions
- Data lineage tracking (source → transformation → consumption)
- Search and discovery interface for business users
- Metadata enrichment (tags, classifications, sensitivity labels)
- Catalog coverage tracking (% of assets documented)
- Usage analytics (who accesses what, how often)
- Integration with BI/analytics tools (catalog-aware queries)
Domain 3: Access Control
- Role-based access control (RBAC) with regular review
- Data classification enforcement (labels drive permissions)
- Least privilege principle (minimal default access)
- Access request and approval workflows
- Privileged access management (admin accounts monitored)
- Access certification (quarterly re-certification of permissions)
- Anomaly detection (unusual access patterns flagged)
- De-provisioning automation (access removed on role change/exit)
Domain 4: Compliance Mapping
- Regulation inventory (which laws apply, by geography and industry)
- Control-to-regulation mapping (which controls satisfy which requirements)
- Data processing records (Article 30 GDPR / equivalent)
- Consent management (capture, storage, withdrawal tracking)
- Data subject rights automation (access, deletion, portability)
- Cross-border transfer compliance (SCCs, adequacy decisions)
- Breach notification procedures (72-hour GDPR, state-specific)
- Regular compliance audits (internal + third-party)
Domain 5: Retention & Lifecycle
- Retention schedule by data type (contractual, regulatory, operational)
- Automated archival pipelines (hot → warm → cold → delete)
- Legal hold management (litigation preservation)
- Deletion verification (confirmed purge with audit trail)
- Storage cost optimization (tiered storage aligned to access patterns)
- Backup and recovery testing (regular restore drills)
- Data minimization enforcement (collect only what is needed)
- End-of-life procedures for decommissioned systems
Domain 6: AI/Agent Data Governance
- Training data provenance tracking (source, consent, bias review)
- Model input/output logging (what went in, what came out)
- PII detection and masking in agent workflows
- Hallucination monitoring (output accuracy validation)
- Agent decision audit trail (explainability for automated decisions)
- Data feedback loops (human review of agent data modifications)
- Vendor data sharing agreements (what third-party APIs see your data)
- Synthetic data policies (when and how to use generated data)
Cost of Poor Governance
| Risk | Average Cost | Prevention Cost |
|---|---|---|
| GDPR fine | $4.3M (average 2025) | $45K-$120K/year |
| Data breach | $4.88M (IBM 2025) | $60K-$200K/year |
| Failed audit | $150K-$500K remediation | $30K-$80K/year |
| Bad data decisions | 15-25% revenue impact | $20K-$60K/year |
| AI bias incident | $2M-$50M (litigation + brand) | $25K-$75K/year |
Remediation Priority Matrix
Always fix in this order:
- Compliance gaps — regulatory fines are existential
- Access control — breaches destroy trust overnight
- AI governance — fastest-growing risk category
- Data quality — garbage in = garbage out at scale
- Cataloging — you cannot govern what you cannot find
- Retention — storage costs compound, legal risk accumulates
Industry Benchmarks (2026)
| Industry | Avg Governance Score | Top Quartile | Regulatory Pressure |
|---|---|---|---|
| Financial Services | 68% | 85%+ | Extreme (SOX, PCI, GDPR) |
| Healthcare | 62% | 80%+ | High (HIPAA, FDA, state) |
| SaaS/Tech | 55% | 78%+ | Growing (SOC 2, GDPR, CCPA) |
| Manufacturing | 45% | 70%+ | Moderate (ITAR, ISO) |
| Retail/Ecommerce | 48% | 72%+ | Growing (PCI, CCPA, GDPR) |
Next Steps
Need a complete data governance implementation tailored to your industry?