Data governance is the framework that defines who can take what actions, on what data, under what circumstances, using what methods. It establishes accountability, policies, and procedures for managing enterprise data assets.
Core Components of Data Governance
1. Data Ownership: Assigning accountability for data assets to specific individuals or teams
2. Data Stewardship: Day-to-day management and quality oversight
3. Data Policies: Rules governing data usage, retention, and access
4. Data Standards: Naming conventions, formats, and definitions
5. Data Catalog: Inventory of data assets with metadata
Key Governance Domains
- Data Quality: Ensuring data meets defined standards
- Data Security: Protecting sensitive information
- Data Privacy: Compliance with regulations (GDPR, CCPA)
- Master Data Management: Maintaining single source of truth
- Metadata Management: Documenting data lineage and definitions
Why Data Governance Matters
- Compliance: Meet regulatory requirements (GDPR, HIPAA, SOX)
- Trust: Users can rely on data for decisions
- Efficiency: Reduce time spent searching for and validating data
- Risk Reduction: Prevent data breaches and misuse
Modern Data Governance Tools
- Atlan: Modern data governance and catalog platform
- Alation: Data intelligence and cataloging
- Collibra: Enterprise data governance
- Databricks Unity Catalog: Governance for lakehouse
- Snowflake Horizon: Governance features in Snowflake
Data Governance Framework
| Role | Responsibility |
|------|----------------|
| Data Owner | Strategic decisions, accountability |
| Data Steward | Quality, standards, day-to-day |
| Data Custodian | Technical implementation, security |
| Data User | Responsible use, feedback |