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Writer's pictureCher Fox

DMBoK Figure 14 Context Diagram: Data Governance and Stewardship

Data Governance (DG) is defined as the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets. All organizations make decisions about data, regardless of whether they have a formal Data Governance function. Those that establish a formal Data Governance program exercise authority and control with greater intentionality (Seiner, 2014). Such organizations are better able to increase the value they get from their data assets.


The Data Governance function guides all other data management functions. The purpose of Data Governance is to ensure that data is managed properly, according to policies and best practices (Ladley, 2012). While the driver of data management overall is to ensure an organization gets value out of its data, Data Governance focuses on how decisions are made about data and how people and processes are expected to behave in relation to data. The scope and focus of a particular data governance program will depend upon organizational needs, but most programs include:

  • Strategy: Defining, communicating, and driving execution of Data Strategy and Data Governance Strategy

  • Policy: Setting and enforcing policies related to data and Metadata management, access, usage, security, and quality

  • Standards and quality: Setting and enforcing Data Quality and Data Architecture standards

  • Oversight: Providing hands-on observation, audit, and correction in key areas of quality, policy and data management (often referred to as stewardship)

  • Compliance: Ensuring the organization can meet data-related regulatory compliance requirements

  • Issue management: Identifying, defining, escalating, and resolving issues related to data security, data access, data quality, regulatory compliance, data ownership, policy, standards, terminology, or data governance procedures

  • Data management projects: Sponsoring efforts to improve data management practices

  • Data asset valuation: Setting standards and processes to consistently define the business value of data assets

To accomplish these goals, a Data Governance program will develop policies and procedures, cultivate data stewardship practices at multiple levels within the organization, and engage in organizational change management efforts that actively communicate to the organization the benefits of improved data governance and the behaviors necessary to successfully manage data as an asset.


For most organizations, adopting formal Data Governance requires the support of organizational change management, as well as sponsorship from a C-Level executive, such as Chief Risk Officer, Chief Financial Officer, or Chief Data Officer.


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