Your IP: Unknown · Your Status: ProtectedUnprotectedUnknown
Data validation

Data validation

Data validation definition

Data validation refers to the process of ensuring that data is accurate, complete, and consistent before it is used for a specific purpose. The goal of data validation is to identify and correct any errors or discrepancies in the data to ensure its quality and reliability.

See also: data backup, integrity checking

Data validation techniques:

  • Format validation. Verifying that the data is in the correct format, such as date, time, or currency.
  • Completeness validation. Ensuring that all required fields are filled out and that there are no missing values.
  • Range validation. Verifying that the data falls within an acceptable range of values.
  • Cross-field validation. Ensuring that the data in one field is consistent with the data in another related field.
  • Business rule validation. Verifying that the data follows specific business rules or requirements.

Data validation process:

  • Defining validation criteria that the data will be checked against such as format, completeness, range, consistency, and business logic.
  • Gathering data may involve importing data from external sources or entering data manually.
  • Applying validation rules manually or via software to check for errors or inconsistencies.
  • Identifying and correcting the errors. The errors may be categorized based on their severity and priority and corrected either manually or using software.
  • Revalidating the data after the errors have been corrected is necessary to ensure that the data is accurate, complete, and consistent.

Ultimate digital security

We value your privacy

This website uses cookies to provide you with a safer and more personalized experience. By accepting, you agree to the use of cookies for ads and analytics, in line with our Cookie Policy.