Less Than Field Anomaly Reporting
How the Less Than Field check reports violations: the anomaly messages it produces, what the numbers mean, how the offending value appears in Source Records, and how to replace the default message with a value from your own data.
Anomaly Messages
At 100% coverage, Less Than Field reports violating rows as Record Anomalies. Below 100% coverage, a failed coverage assertion produces one Shape Anomaly for the dataset. The two templates are:
Record Anomaly
The field '<field_name>' has value <row_value>, which is not less than the value of '<compared_field>'
Shape Anomaly
When a filter is set, both Record and Shape Anomaly messages end with [filter: <expression>].
Scan settings can group a large number of Record Anomalies into one rolled-up Shape Anomaly. This behavior applies across rule types and is documented under Maximum Record Anomalies per Check.
What the Numbers Mean
- X.XXX%: the fraction of filtered rows where the relationship does not hold.
- N: the total number of rows the check evaluated (after the filter, if any). Rows where a side is NULL count in this total; whether they pass depends on the comparator, as described in NULL Handling.
- K: the number of rows where the relationship does not hold.
Source Records Behavior
The offending cell of the target field is highlighted with an orange outline and an orange-tinted background in the Source Records view. The compared field renders normally, so read both columns side by side to see why the row failed.
Custom Anomaly Description
Less Than Field supports Custom Anomaly Description because it emits Record Anomalies. When anomaly_message_field (or the Custom Anomaly Description toggle in the UI) is set to another column on the same row, the Record Anomaly message becomes the value of that column for the violating row. When the referenced column is null, missing, or empty, the standard template is used instead.
Because the option only applies to Record Anomalies, it does not affect Shape Anomalies, which always use the fixed template.
See Also
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How It Works
The complete reference: definition, field scope, the compared field, comparators, NULL handling, filter behavior, and coverage.
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Examples
Three production scenarios with sample data, anomaly messages, and the SQL equivalent of what the check evaluates.
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Best Practices
Guidelines for choosing the compared field, using tolerance, and keeping the signal clean.
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Permissions
The team permission each action needs: view, create, edit, archive, restore, and delete.