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DMBoK Figure 15 Data Governance and Data Management

Just as an auditor controls financial processes but does not actually executive financial management, data governance ensures data is properly managed without directly executing data management. Data governance represents an inherent separation of duty between oversight and execution.

A data-centric organization values data as an asset and manages data through all phases of its lifecycle, including project development and ongoing operations. To become data-centric, and organization must change the way it translates strategy into action. Data is no longer treated as a by-product of process and applications. Ensuring data is of high quality is a goal of business processes. As organizations strive to make decisions based on insights gained from analytics, effective data management becomes a very high priority.


People tend to conflate data and information technology. To become data-centric, organizations need to think differently and recognize that managing data is different from managing IT. This shift is not easy. Existing culture, with its internal politics, ambiguity about ownership, budgetary competition, and legacy systems, can be a huge obstacle to establishing an enterprise vision of data governance and data management.


While each organization needs to evolve its own principles, those that seek to get more value from their data are likely to share the following:

  • Data should be managed as a corporate asset

  • Data management best practices should be incented across the organization

  • Enterprise data strategy must be directly aligned with overall business strategy

  • Data management processes should be continuously improved

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