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Principle 17 - Applications Ensuring Data Quality

Applications must help ensure valid, consistent, and secure data.

Note

As used here, the terms "valid" and "consistent" refer to data which satisfies a set of business rules. Documentation defines what is valid and consistent for a data element or set of related elements. Data which is valid may or may not be accurate (that is, "correct" or "factual"). Applications cannot verify the accuracy of the data.

 Rationale

It is unreasonable to place the full burden of data validity and consistency on manual operating procedures or the quality of the training provided for the users of the application. Applications are the vehicles for creating and using data and are therefore uniquely positioned to help ensure the validity and consistency of the data.

 Implications

  • The application's creation and use of data must conform to the rules for that data as specified in the University data architecture.
  • The application is only one of several possible vehicles for verifying data validity (database tools such as active dictionaries are another). These vehicles must work together to ensure optimum results.
  • Similarly, the application is only one of several possible vehicles that can be used to secure data and these tools must work together to ensure optimum results. Security restrictions implemented at the application level must follow standards for security and confidentiality but should not inhibit flexibility or ease of use.
  • Wherever possible, common data validation routines should be developed as reusable components are shared by multiple applications.
  • It is not always possible nor desirable, given cost/benefit or operational considerations, for an application to verify data completely or immediately. The application's role in validating data lessens the burden but does not lessen the responsibility of individual users for ensuring overall data quality. Associated training and support for users are ongoing requirements.
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