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  2. Data quality - Wikipedia

    en.wikipedia.org/wiki/Data_quality

    Data quality control is the ... a platform for collaboration amongst subject experts on data quality and data governance around the world to build and maintain global ...

  3. Data integrity - Wikipedia

    en.wikipedia.org/wiki/Data_integrity

    An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...

  4. Master data management - Wikipedia

    en.wikipedia.org/wiki/Master_data_management

    The Data Owner is responsible for the requirements for 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.

  5. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    The result is a new cycle in the data-cleansing process where the data is audited again to allow the specification of an additional workflow to further cleanse the data by automatic processing. Good quality source data has to do with “Data Quality Culture” and must be initiated at the top of the organization.

  6. Quality of Data - Wikipedia

    en.wikipedia.org/wiki/Quality_of_Data

    Quality of Data (QoD) is a designation coined by L. Veiga, that specifies and describes the required Quality of Service of a distributed storage system from the Consistency point of view of its data. It can be used to support big data management frameworks, Workflow management, and HPC systems (mainly for data replication and consistency). It ...

  7. 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.

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