What is Data Governance?
Data governance is the framework of policies, processes, and standards for managing data assets across an organization.
Data governance is the framework of policies, processes, and standards for managing data assets across an organization. It covers data quality, data access, data privacy, data lifecycle, and data compliance.
Key governance components: data catalog (inventory of all data assets), data lineage (how data flows and transforms), access controls (who can see what), quality checks (automated validation), retention policies (how long data is kept), and privacy compliance (GDPR, CCPA, HIPAA).
Data governance is increasingly important because: regulatory requirements are expanding (GDPR fines up to 4% of global revenue), AI systems require high-quality training data, data breaches are expensive ($4.5M average cost in 2024), and poor data quality leads to wrong decisions.
For product teams, governance means: knowing what data you collect, why you collect it, who has access, how long you keep it, and how you protect it.
Why It Matters
Data governance is a regulatory requirement and a business necessity. Organizations without governance face regulatory fines, data quality issues, security breaches, and inability to trust their own analytics.
Frequently Asked Questions
What is data governance?
The framework of policies and processes for managing data: quality, access, privacy, lifecycle, and compliance. It ensures data is accurate, secure, and used responsibly.
Is data governance required by law?
Effectively yes. GDPR, CCPA, HIPAA, and industry regulations require data management practices that constitute governance. Fines can reach 4% of global revenue.
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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