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A professional-level summary covering key definitions, frameworks, and exam-relevant points.
Data Governance: Definition, Framework, and Implementation
According to the DAMA DMBOK v2, Data Governance is "the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets." It is the highest-level knowledge area in the DAMA framework — the discipline that provides direction and oversight to all other data management functions.
Core Components of a Data Governance Framework
A mature data governance framework encompasses six core components: Data Governance Strategy (the vision, goals, and roadmap), Data Governance Organisation (the roles, responsibilities, and decision-making structures), Data Governance Policies (the rules and standards), Data Governance Processes (the workflows for implementing and enforcing policies), Data Governance Tools (the technology supporting governance activities), and Data Governance Metrics (the KPIs measuring governance effectiveness).
Key Roles in Data Governance
| Role | Responsibility |
|---|---|
| Chief Data Officer (CDO) | Executive accountability for data as a strategic asset |
| Data Governance Council | Cross-functional body setting data strategy and resolving disputes |
| Data Owner | Business leader accountable for a specific data domain |
| Data Steward | Operational responsibility for data quality and standards in a domain |
| Data Custodian | Technical responsibility for data storage, security, and access |
| Data Governance Manager | Programme management and coordination of governance activities |
The Business Case for Data Governance
Organisations implement data governance to achieve several business outcomes: regulatory compliance (GDPR, CCPA, HIPAA, SOX), improved data quality leading to better decision-making, reduced data management costs through standardisation, increased trust in data across the organisation, and risk reduction through proper data security and access controls.
Data Governance vs Data Management
Data governance is a subset of data management — specifically, the authority and control layer. Data management encompasses all activities related to data throughout its lifecycle; data governance provides the framework of accountability and decision-making within which those activities occur. The CDMP exam tests this distinction carefully.
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