Uniqueness Validation

Use uniqueness validation to ensure that each value for a given field is unique across all datasets within a Data Standards Cloud account. When you create or edit a field, you can set that field as unique. Then, during submission, in the validation step, we check all datasets where the field is used to see if a given value already exists. If so, an error displays in the paused-pending submission, saying that the value is not unique and prompting the user to correct the value before completing the submission.

Supported Field Types

• Text
• Concatenations
• Patterns

Enabling Uniqueness

You can set a field as unique in the Field Settings menu by checking the Require Uniqueness option. This is true both when you create new fields and when you edit existing fields.

Note: Once uniqueness is enabled for an existing field, uniqueness validation runs to mark all existing values for that field across datasets for uniqueness verification in future submissions. If any submissions are attempted while this validation is running, the submission will fail with an error message instructing the user to retry the submission.

Similarly, you can set patterns as unique in Pattern Settings.

Uniqueness Validation Considerations

Dataset Data Versus Pending

Uniqueness validation references successfully processed data in datasets, not data contained on failed submissions in Pending. For example, if a submission is created with three rows of data containing unique field values, and that submission fails, those three unique values could be entered into the product on another submission that is successfully processed. Those three values entered on the failed submission (that once were unique) will need to be updated for that submission to successfully process.

Submissions

Uniqueness checks run on any change to data via submission, new or edited. For example, if a new submission contains a duplicate value, the submission will fail. Or, if a submission attempts to edit a value that is unique to something that is not unique, the submission will fail.

Additionally, if duplicate data is entered on a single submission, the submission will fail and any duplicate values will be highlighted with an error.

Universal Across Datasets

When configuring a field to validate for unique values, all values associated with that field across all datasets are checked. For example, if you have two datasets, Dataset A and Dataset B, and the field that is configured to validate unique values is shared across both, all values must be unique across both.

Case Sensitivity

Uniqueness validation is case-sensitive.