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  2. Data governance - Wikipedia

    en.wikipedia.org/wiki/Data_governance

    Here data governance is a data management concept concerning the ... Examples of these ... Examples of commonly referenced best practices and ...

  3. Generally Accepted Recordkeeping Principles - Wikipedia

    en.wikipedia.org/wiki/Generally_Accepted...

    The maturity model will be most useful to leaders who wish to achieve the maximum benefit from their information governance practices. Effective information governance requires a continuous focus. But in order to get started, organizations can look to the steps below: Identify the gaps between the organization's current practices and the ...

  4. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    However, data has to be of high quality to be used as a business asset for creating a competitive advantage. Therefore, data governance is a critical element of data collection and analysis since it determines the quality of data while integrity constraints guarantee the reliability of information collected from data sources.

  5. Enterprise data management - Wikipedia

    en.wikipedia.org/wiki/Enterprise_data_management

    Enterprise data management (EDM) is the ability of an organization to precisely define, easily integrate and effectively retrieve data for both internal applications and external communication. EDM focuses on the creation of accurate, consistent, and transparent content.

  6. Information governance - Wikipedia

    en.wikipedia.org/wiki/Information_governance

    Information governance, or IG, is the overall strategy for information at an organization. Information governance balances the risk that information presents with the value that information provides. Information governance helps with legal compliance, operational transparency, and reducing expenditures associated with legal discovery. An ...

  7. Data steward - Wikipedia

    en.wikipedia.org/wiki/Data_steward

    The data steward may also serve as a liaison between the organization's data users and technical teams, helping to bridge the gap between business needs and technical requirements. They may also play a role in educating others within the organization about best practices for data management, and advocating for data-driven decision-making.

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