Data Governance
The framework of policies, processes, and standards for managing data assets. Ensures data is accurate, secure, compliant, and used appropriately across the organization.
In-Depth Explanation
Data governance establishes the rules and responsibilities for managing data as a valuable organizational asset. It covers data quality, security, privacy, and appropriate use.
Governance components:
- Policies: Rules for data handling
- Standards: Consistent definitions and formats
- Processes: Workflows for data management
- Roles: Ownership and accountability
- Technology: Tools supporting governance
Key governance areas:
- Data quality management
- Data security and access control
- Privacy and compliance (GDPR, CCPA, state privacy laws)
- Data cataloging and discovery
- Master data management
- Data lifecycle management
Governance frameworks:
- DAMA-DMBOK (Data Management Body of Knowledge)
- DCAM (Data Management Capability Assessment Model)
- Custom frameworks based on needs
Business Context
Governance reduces risk, ensures compliance with US regulations like CCPA and HIPAA, and maximizes data value. Essential as AI expands data usage across organizations.
How Clever Ops Uses This
We help US businesses establish data governance appropriate for their size and AI ambitions, balancing control with agility while meeting federal and state compliance requirements.
Example Use Case
"Implementing governance that defines who can access customer data, how long it's retained, and ensures AI models comply with privacy requirements."