The DAMA Wheel represents the principal Data Management Knowledge Areas defined by DAMA-DMBOK2. Data Governance occupies the central position because governance provides authority, coordination, standards, and oversight across the other disciplines. The surrounding areas include Data Architecture, Data Modeling and Design, Data Storage and Operations, Data Security, Data Integration and Interoperability, Document and Content Management, Reference and Master Data, Data Warehousing and Business Intelligence, Metadata Management, and Data Quality. DAMA descriptions of the framework identify these as Knowledge Areas rather than project deliverables or maturity dimensions.

The Wheel is deliberately integrative. No Data Management discipline operates effectively in complete isolation. For example, Data Quality relies on Governance for authority and accountability, Metadata Management for definitions and lineage, Reference and Master Data for consistent shared entities and codes, Data Architecture for structural context, and Integration for controlled movement between systems.

This interaction is central to Chapter 13. Data Quality cannot be reduced to cleansing defective records after problems appear. Sustainable quality requires coordinated management throughout the lifecycle and across the other DAMA knowledge areas.

Data management processes, deliverables, strategic initiatives, and maturity assessments are all legitimate DAMA concepts, but they are not what the DAMA Wheel itself principally represents.

Reference Topics: DAMA-DMBOK2 Chapter 1 — DAMA-DMBOK Framework; DAMA Wheel; Knowledge Areas; Chapter 3 — Governance; Chapter 13 — Data Quality Relationships with Other Knowledge Areas.

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