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Data Governance

Best Practices for Implementing Data Governance in 2025

Proven best practices for implementing data governance: executive sponsorship, starting with CDEs, building incrementally, measuring value, and avoiding common pitfalls.

CDMP Master Academy·9 March 2025·11 min read

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A professional-level summary covering key definitions, frameworks, and exam-relevant points.

Implementation Framework

The DAMA DMBOK v2 recommends a phased approach to data governance implementation, starting with programme design, moving through initial deployment, and evolving into a mature, enterprise-wide programme. The key phases are: assess current state, define governance vision and strategy, design the governance framework, implement initial governance (CDEs and priority domains), expand coverage, and continuously improve.

Common Implementation Pitfalls

PitfallConsequencePrevention
No executive sponsorProgramme ignored, overridden by business prioritiesSecure CDO or senior VP sponsorship before starting
Boiling the oceanProgramme overwhelmed, no early winsStart with 20–30 CDEs, expand gradually
IT-led governanceBusiness disengaged, policies not adoptedBusiness-led governance with IT support
No measurementCannot demonstrate value, loses fundingDefine and track metrics from day one
Governance as a projectProgramme deteriorates after initial implementationBuild as a permanent programme with ongoing roles

CDMP Exam Relevance

Implementation best practices appear in CDMP scenario questions that ask candidates to identify the most appropriate next step in a governance programme, or to diagnose why a governance programme is failing. The distinction between governance as a programme (ongoing) versus a project (one-time) is a frequently tested concept.

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