Introduction to the Any Not Null Check
The Any Not Null check asserts that at least one of the selected fields holds a value on every row. Use it when several fields are individually optional but a row with none of them is incomplete, such as a customer with no contact method or an applicant with no identifier.
This section is the complete guide to the check. The Deep Dive covers the definition, properties, and full evaluation semantics, explains how anomalies are reported, walks through production examples, and collects best practices; the How-tos are step-by-step tutorials for creating, editing, and deleting a check; the API page documents the payload for programmatic use; and the FAQ answers the most frequent questions.
Next Steps
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How It Works
The complete reference: definition, field scope, properties, evaluation flow, NULL handling, filter behavior, and coverage.
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Anomaly Reporting
The anomaly messages the check produces, what the numbers mean, Source Records highlighting, and Custom Anomaly Description.
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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 grouping interchangeable fields, handling empty strings, pairing rules, and keeping the signal clean.
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Permissions
The team permission each action needs: view, create, edit, archive, restore, and delete.
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Create a Check
Step-by-step tutorial for creating an Any Not Null check across two or more fields.
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Edit a Check
Step-by-step tutorial for adding or removing fields, or changing the filter, coverage, or organizational properties.
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Delete a Check
Step-by-step tutorial for archiving a check and deleting it permanently.
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Troubleshooting
Common problems with empty strings, over-broad field groups, and anomaly reporting, and how to resolve them.
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API
Payload shape and field notes for creating an Any Not Null check programmatically.
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FAQ
Short answers to questions about NULLs, field selection, coverage, and anomaly reporting.