Data governance establishes the policies, processes, and responsibilities for managing data assets, ensuring their quality, integrity, security, and usability across the enterprise to support strategic objectives and regulatory compliance.
Context for Technology Leaders
For CIOs and Enterprise Architects, robust data governance is critical for maintaining data trust and enabling data-driven decision-making. It underpins initiatives like AI adoption, cloud migration, and digital transformation, aligning with frameworks such as DAMA-DMBOK and GDPR to ensure data assets are managed effectively and ethically, mitigating risks and maximizing value.
Key Principles
- 1Data Quality: Ensuring accuracy, completeness, and consistency of data through defined standards and validation processes.
- 2Data Security & Privacy: Implementing controls and policies to protect sensitive data from unauthorized access, breaches, and misuse, adhering to regulations.
- 3Data Stewardship: Assigning clear roles and responsibilities for data assets, promoting accountability and ownership across business units.
- 4Metadata Management: Documenting data definitions, lineage, and usage to enhance understanding, discoverability, and effective utilization of information assets.
- 5Compliance & Ethics: Establishing guidelines and practices to meet regulatory requirements (e.g., GDPR, HIPAA) and ethical considerations in data handling.
Related Terms
Data ManagementData QualityMaster Data ManagementData StewardshipInformation Lifecycle ManagementData Catalog