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A professional-level summary covering key definitions, frameworks, and exam-relevant points.
DMBOK Governance Principles
The DAMA DMBOK v2 identifies several core data governance principles that should underpin any governance programme. These principles reflect the values of the data management profession and provide the philosophical foundation for governance policies and decisions.
Key Principles and Their Governance Implications
| Principle | Governance Implication |
|---|---|
| Accountability | Every data domain must have a named Data Owner with formal accountability |
| Transparency | Governance decisions and policies must be documented and communicated |
| Integrity | Data quality standards must be defined, measured, and enforced |
| Stewardship | Data Stewards must be appointed and empowered for each domain |
| Compliance | Governance programme must map to regulatory requirements |
| Standardisation | Common data definitions and formats must be established and enforced |
| Collaboration | Governance council must include both business and IT representation |
| Value | Governance ROI must be measured and reported to executive sponsors |
| Proportionality | Critical Data Elements (CDEs) receive highest governance priority |
| Continuous Improvement | Governance maturity must be assessed and improvement plans maintained |
CDMP Exam Relevance
Governance principles appear in CDMP questions that ask candidates to evaluate governance programme designs or identify which principle is being violated in a scenario. The proportionality principle is particularly frequently tested — questions often describe a scenario where excessive governance is being applied to low-value data, and ask which principle is being violated.