The DAMA DMBOK Framework

What is the DMBOK?

Data Management Body of Knowledge (DAMA-DMBOK Guide) is a collection of processes and best practices within the Data Management and Data Goverance area. The DMBOK contains generally accepted as best practices and references for each Data Management discipline.

Data Management (DM) is an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. These processes overlap and interact within each data management knowledge area.

THE PURPOSE OF THE DMBOK

The current DM environment can be a confusing combination of terms, methods, tools, opinion, and hype.

To mature this discipline, DAMA International’s Guide to the Data Management Body of Knowledge (DAMA-DMBOK) provides concepts and capability maturity models for the standardization of:

Activities, processes, and best practices
Roles and responsibilities
Deliverables and metrics
A maturity model

Standardization of data management disciplines will help data management professionals perform more effectively and consistently.

The 11 Data Management Knowledge Areas are:

Data Governance –planning, oversight, and control over management of data and the use of data and data-related resources. While we understand that governance covers ‘processes’, not ‘things’, the common term is Data Governance.
Data Architecture –the overall structure of data and data-related resources as an integral part of the enterprise architecture
Data Modeling & Design –analysis, design, building, testing, and maintenance
Data Storage & Operations –structured physical data assets storage deployment and management
Data Security –ensuring privacy, confidentiality and appropriate access to PII, PHI and an individuals private data. Ensuring network security as well
Data Integration & Interoperability –acquisition, extraction, transformation, movement, delivery, replication, federation, virtualization and operational support
Documents & Content –storing, protecting, indexing, and enabling access to data found in unstructured sources (electronic files and physical records), and making this data available for integration and interoperability with structured (database) data.
Reference & Master Data –Managing shared data to reduce redundancy and ensure better data quality through standardized definition and use of data values.
Data Warehousing & Business Intelligence –managing analytical data processing and enabling access to decision support data for reporting and analysis.
Metadata–collecting, categorizing, maintaining, integrating, controlling, managing, and delivering metadata.
Data Quality –defining, monitoring, maintaining data integrity, and improving data quality.

Data Management Knowledge Areas

DAMA-DMBOK: Data Management Body of Knowledge

Today’s organizations recognize that managing data is central to their success. They recognize the value of their data and seek to leverage that value. As human capacity to create and exploit data has increased, so too has the need for reliable data management practices. This is what the DAMA-DMBOK is all about, among also the theory for the CMDP certification. Read more...

Navigating the Labyrinth

Navigating the Labyrinth is a concise guide to data management, providing an executive’s overview to the DMBOK2. If you are leading an organization or if you need to communicate with leaders about data management, Navigating the Labyrinth is your guide. Read more…