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  2. Data governance - Wikipedia

    en.wikipedia.org/wiki/Data_governance

    A data steward is a role that ensures that data governance processes are followed and that guidelines are enforced, and recommends improvements to data governance processes. Data governance involves the coordination of people, processes, and information technology necessary to ensure consistent and proper management of an organization's data ...

  3. Category : Country data templates of international organizations

    en.wikipedia.org/wiki/Category:Country_data...

    If the template has a separate documentation page (usually called "Template:template name/doc"), add [[Category:Country data templates of international organizations]] to the <includeonly> section at the bottom of that page.

  4. Data quality - Wikipedia

    en.wikipedia.org/wiki/Data_quality

    Data Quality (DQ) is a niche area required for the integrity of the data management by covering gaps of data issues. This is one of the key functions that aid data governance by monitoring data to find exceptions undiscovered by current data management operations.

  5. Data steward - Wikipedia

    en.wikipedia.org/wiki/Data_steward

    A data steward is an oversight or data governance role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization's data assets, including the metadata for those data assets.

  6. MIKE2.0 methodology - Wikipedia

    en.wikipedia.org/wiki/MIKE2.0_Methodology

    Information governance is a term used in MIKE2.0. The governance model provides assessment tools, information standards, organizational structures and roles and responsibilities in relation to managing information assets. Governance 2.0 is another term used, along with Enterprise 2.0 techniques and technologies.

  7. Master data management - Wikipedia

    en.wikipedia.org/wiki/Master_data_management

    The Data Owner is responsible for the requirements for data definition, data quality, data security, etc. as well as for compliance with data governance and data management procedures. The Data Owner should also be funding improvement projects in case of deviations from the requirements.