Data and information management is a broad and complex field. Data is both a strategic asset and a regulatory liability. With rapid advances in AI, both value and risk are amplifying. Now, more than ever before, we need structure and frameworks to guide data management and data use. DMBOK, DCAM, and TOGAF are three of the most respected frameworks in the space, and we often hear discussion and debate about which to choose. This “choose one” thinking leads to suboptimal data management based on the misguided assumption that DMBOK, DCAM, and TOGAF are alternatives. The truth is that they each serve distinct purposes. They are not alternatives or competing models, but complementary parts of holistic data management.

• DMBOK defines the what and why of data management — a knowledge base of best practices across 11 data domains.
• DCAM examines how well data is managed – a structured capability and maturity model to assess and improve data management performance.
• TOGAF describes how to architect data management – a methodology to align business and IT architectures across data, systems, and processes.

Choosing only one framework is the path to isolated solutions and an incomplete approach to data management. You’ll solve part of the problem but leave major gaps elsewhere. Using DMBOK without DCAM supports knowing what to do, but not how to assess whether you’re doing it well or where to improve. DCAM without DMBOK supports maturity assessment but lacks detailed knowledge to guide improvements. TOGAF without DCAM and DMBOK provides an architectural foundation but lacks the rigor needed for data-specific challenges, such as governance, lineage, and quality.

The three frameworks described here are complementary, not competitive. Together, the frameworks align strategic objectives (via TOGAF), data management best practices (via DMBOK), and data capabilities and operational performance (via DCAM). DMBOK, DCAM, and TOGAF work best when deployed together to manage data from multiple perspectives.
Collectively, they provide the structure to:

• Define data management practices (DMBOK)
• Measure and improve data management capabilities (DCAM)
• Integrate practices and capabilities into enterprise architecture (TOGAF)

In the increasingly complex and rapidly changing world of data management, well-rounded and versatile information management professionals will have knowledge of all three frameworks.

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