DAMA-DMBOK Wheel¶

Definition¶

The DAMA-DMBOK Wheel is DAMA International's reference taxonomy for data management, placing Data Governance at the hub and arranging ten further knowledge areas - 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 Management - around it as interconnected disciplines rather than isolated silos.

Explanation¶

The wheel is the organizing device behind the DAMA Guide to the Data Management Body of Knowledge (DMBOK2, revised 2024): every discipline a data organization runs, from architecture to quality, is drawn as a spoke that depends on and feeds back into governance at the center, rather than as a standalone function with its own mandate. Because the ten knowledge areas and their governance-centric arrangement have held constant across the second edition and its 2024 revision, the wheel functions less as a diagram to memorize than as a checklist: a team can lay its current data initiatives against the ten spokes to see which disciplines are unstaffed or ungoverned, and use the shared vocabulary to compare maturity across teams. DAMA's 2024 Evolved Wheel variant extends the same hub-and-spoke logic to newer areas such as ethics, big data and data science without changing the underlying structure.

Key Properties¶

Data Governance sits at the hub; ten other knowledge areas (architecture, modeling, storage and operations, security, integration and interoperability, document and content management, reference and master data, warehousing and BI, metadata, quality) sit as coordinated spokes
The disciplines are framed as interconnected functions, not isolated silos - each spoke both depends on and feeds governance
Serves as a shared vocabulary and maturity-assessment checklist across teams, not a set of how-to procedures for any one discipline
The 2024 Evolved Wheel extends the same hub-and-spoke structure to newer areas (ethics, big data, data science) rather than replacing it

Relationships¶

No relationships recorded yet.

Applications¶

Auditing a data program's coverage by checking which of the ten spokes have no owner or process; using the wheel's shared vocabulary to align data, engineering and governance teams on scope before writing a data strategy; framing a maturity assessment or roadmap around the ten knowledge areas instead of an ad hoc list of initiatives.

Sources¶

https://dama-phoenix.org/education/the-dama-dmbok-wheel/
https://dama.org/learning-resources/dama-data-management-body-of-knowledge-dmbok/