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  2. 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 ...

  3. Data validation - Wikipedia

    en.wikipedia.org/wiki/Data_validation

    Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...

  4. Data validation and reconciliation - Wikipedia

    en.wikipedia.org/wiki/Data_validation_and...

    Data reconciliation is a technique that targets at correcting measurement errors that are due to measurement noise, i.e. random errors.From a statistical point of view the main assumption is that no systematic errors exist in the set of measurements, since they may bias the reconciliation results and reduce the robustness of the reconciliation.

  5. 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.

  6. Validity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Validity_(statistics)

    Validity is the main extent to which a concept, conclusion, or measurement is well-founded and likely corresponds accurately to the real world. [1] [2] The word "valid" is derived from the Latin validus, meaning strong.

  7. Data collection - Wikipedia

    en.wikipedia.org/wiki/Data_collection

    Data collection and validation consist of four steps when it involves taking a census and seven steps when it involves sampling. [3] A formal data collection process is necessary, as it ensures that the data gathered are both defined and accurate. This way, subsequent decisions based on arguments embodied in the findings are made using valid ...

  8. Data auditing - Wikipedia

    en.wikipedia.org/wiki/Data_auditing

    Data auditing can also refer to the audit of a system to determine its efficacy in performing its function. For instance, it can entail the evaluation of the information systems of the IT departments to determine whether they are effective in protecting the integrity of critical data. [ 2 ]

  9. Member check - Wikipedia

    en.wikipedia.org/wiki/Member_check

    In qualitative research, a member check, also known as informant feedback or respondent validation, is a technique used by researchers to help improve the accuracy, credibility, validity, and transferability (also known as applicability, internal validity, [1] or fittingness) of a study. [2]