Choose Your Reading Style
A professional-level summary covering key definitions, frameworks, and exam-relevant points.
DAMA Definition
The DAMA DMBOK v2 defines Data Management as "the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles." It is the umbrella discipline that encompasses all 11 DMBOK knowledge areas.
The DMBOK Wheel
The DMBOK is often represented as a wheel, with Data Governance at the hub and the 10 other knowledge areas as spokes. This visual reinforces the principle that governance provides direction and oversight to all other data management functions. The 10 non-governance knowledge areas are: Data Architecture, Data Modelling and Design, Data Storage and Operations, Data Security, Data Integration and Interoperability, Documents and Content, Reference and Master Data, Data Warehousing and BI, Metadata Management, and Data Quality.
Data Management vs Data Governance
This is one of the most commonly tested distinctions in the CDMP exam. Data governance is the authority and decision-making function — it sets policies, assigns accountability, and monitors compliance. Data management is the execution function — it implements the policies through technical and operational activities. Governance without management is just rules on paper; management without governance is activity without direction.
Strategic Value
The DMBOK frames data as an enterprise asset with measurable value. Effective data management increases this value by improving data quality, reducing duplication, enabling analytics, ensuring compliance, and supporting digital transformation. The CDO and data governance council are responsible for realising this strategic value through coordinated data management programmes.