Data Governance
The framework of policies, processes, and standards for managing data assets. Ensures data is accurate, secure, compliant, and used appropriately across the organisation.
In-Depth Explanation
Data governance establishes the rules and responsibilities for managing data as a valuable organisational 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, Privacy Act)
- 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, and maximises data value. Essential as AI expands data usage across organisations.
How Clever Ops Uses This
We help Australian businesses establish data governance appropriate for their size and AI ambitions, balancing control with agility.
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."
Frequently Asked Questions
Related Terms
Related Resources
Data Quality
The measure of data fitness for its intended purpose. High-quality data is accur...
Data Catalog
A centralised inventory of data assets with metadata, enabling discovery, unders...
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