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Data validation

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Run a validation session using the API

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  • Last UpdatedJun 17, 2026
  • 2 minute read

Data validation works on the simple principal - structure data to test its validity against a set of rules.

Step-by-Step: Running a Validation Session

These are the high level steps, or order of operation, to configure and run a validation session. Description of a transient operation can be found in the Appendix.

A Validation Operation for a Session

  1. Obtain the Access Token The Client ID and Client secret are created by an admin. Contact the admin for this information.

  2. Upload the Class Library

    1. Review or query existing class libraries to understand what is available.

    2. Upload your class library XML file to the cloud.

    3. Once uploaded, the system generates a handle—the primary key for the class library.

  3. Upload the Dataset

    1. Upload the dataset file.

    2. This dataset will later be validated against the rules defined in the class library.

  4. Insert File Mapping

    1. Map your data by connecting:

      • The class library ID handle to the dataset ID handle

    Which tells the system which dataset should be validated against which class library.

  5. Run Consistency Status Check

    1. Execute the GetConsistencyStatus operation.

    2. This check identifies any inconsistencies between the dataset and the class library.

    3. If issues appear, fix them—or explicitly ignore them—before continuing.

  6. Insert a Session

    1. Create a new validation session by defining:

      • The class library ID

      • The dataset ID

      • A session name

      • The vocabulary to use

    2. A new session handle is generated.Note: In the UI, there is an extra step for assigning policies and linking activities to rules, but this is not part of the API workflow.

  7. Start the Session

    • Provide the session ID to start the validation run.

  8. Check Session Status

    • Monitor the status of the running session until it completes.

  9. View Validation Results

    • Once complete, retrieve the output for both:

      • Object-level issues

      • Attribute-level issues

        These results identify specific validation problems in the data.