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Data Governance is a framework of policies, procedures, and standards that ensures data is consistent, accurate, secure, and used responsibly throughout an organization. It defines who can take what action upon what data, in what situations, and using which methods, helping to maintain data quality, compliance, and alignment with overall business objectives.

ome key aspects typically included in a data governance framework:

1. Roles & Responsibilities
   Clear ownership and accountability (e.g., data owners, stewards, custodians) is absolutely crucial for a successful Data Governance. It ensures people know who is responsible for specific data assets and governance activities.

2. Policies & Standards
   Establishes formal rules, procedures, and quality benchmarks for data creation, storage, and usage, ensuring consistency and compliance across the organization.

3. Data Quality Management
   Implements processes and criteria (like accuracy, completeness, and timeliness) to maintain high data quality and trustworthiness.

4. Security & Privacy
   Protects sensitive data through access controls, encryption, and adherence to relevant regulations (e.g., GDPR, HIPAA).

5. Data Lifecycle Management
   Governs data from creation to archival, including retention and disposal practices, ensuring optimal storage and regulatory compliance.

6. Metadata Management
   Captures information (metadata) about data (e.g., definitions, relationships, lineage), enabling efficient data discovery and understanding. Often handled via a Data Catalogue Tool.

7. Monitoring & Auditing
   Continuously tracks compliance, identifies anomalies, and evaluates the effectiveness of governance practices, enabling adjustments as needed.