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Equal To Troubleshooting

Common problems when creating and running an Equal To check, their causes, and how to resolve them.

Validation Fails When Creating the Check

Clicking Validate returns an error instead of a success message.

Cause: The rule could not run against the selected data. The most common reasons are an invalid Filter Clause expression, a connection problem with the source, or a container that failed to load.

Resolution:

  1. Review the error message: it explains what needs attention.
  2. Check the Filter Clause for typos: it must be a valid SQL WHERE expression for the selected container.
  3. If the message says the container is marked as Unloadable, the container was skipped after repeated operation failures. Follow the steps in Unloadable Container Error.

Values That Look Equal Are Flagged

The reported value appears identical to the expected one.

Cause: Without a tolerance the comparison is exact, and a computed number can differ far below the printed precision.

Resolution: Set the Numeric comparator with a margin that matches the arithmetic, for example 0.01 on money.

A Multi-Field Check Fires on One Column

The check reports rows where only one of the selected fields differs.

Cause: Several selected fields are asserted together: all of them must equal the value.

Resolution: That is the intended behavior. Split the check when the fields should be evaluated independently.

Rows With NULL Values Are Flagged

Rows where the selected field is empty are reported as violations, although they carry no wrong value.

Cause: This is by design: the check asserts that each selected field is present and equal to the value, so a NULL fails the comparison.

Resolution: If the empty rows are expected, exclude them with a Filter Clause such as <field> IS NOT NULL, and track presence separately with a Not Null check on the same field. Note that a Numeric comparator changes this: with one set, a row whose selected fields are all NULL passes instead.

The Field Does Not Appear in the Field Picker

The column you want is not listed.

Cause: The picker only lists numeric fields.

Resolution: For a text or date constant, use Expected Values with a single-entry list.

An Edited Check Keeps Behaving the Old Way

You changed the configuration but the anomaly list did not change.

Cause: Edits take effect on the next Scan. Saving the check does not re-evaluate the data, and anomalies raised under the previous configuration are not modified.

Resolution: Run a Scan on the container (or wait for the scheduled one). Old anomalies stay open until you triage them or a Full scan with Auto Resolve clears them. See What Happens to Existing Anomalies.

No Anomalies Although the Data Looks Wrong

A Scan ran, the data clearly breaks the rule, but nothing was reported.

Cause: One of these configurations is excluding the violations:

  • The check is in Draft status: Draft checks are not evaluated by Scans.
  • The Filter Clause excludes those rows before the evaluation runs.
  • Coverage is below 100% and the failing fraction stayed within the tolerance, so the check passed.

Resolution: Confirm the check is Active and test the filter expression against the offending rows. Then review the coverage setting; see Coverage and Tolerance.

Expected One Anomaly per Row, Got a Single Rolled-Up One

Many rows failed, but the scan reported one Shape Anomaly instead of per-row Record Anomalies.

Cause: When the number of failing rows exceeds the scan's rollup threshold, the per-row findings are grouped into one rolled-up Shape Anomaly.

Resolution: This is expected behavior; the rolled-up anomaly carries sampled source records. To change the threshold, see Maximum Record Anomalies per Check.