Not Null Anomaly Reporting

How the Not Null check reports violations: the anomaly messages it produces, what the numbers mean, how the missing value appears in Source Records, and how to replace the default message with a value from your own data.

Anomaly Messages

At 100% coverage, Not Null 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 a null or missing value

Shape Anomaly

For the field '<field_name>', X.XXX% of N records (K) have null or missing values

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 with at least one empty field.
• N: the total number of rows the check evaluated (after the filter, if any).
• K: the number of rows with at least one empty field.

Source Records Behavior

The empty cell is highlighted with an orange outline and an orange-tinted background in the Source Records view, mirroring the platform's standard violation rendering. On a multi-field check, every selected field that is empty on the violating row is highlighted; fields outside the check render normally.

Custom Anomaly Description

Not Null 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