Introduction to the Sum Check
The Sum check asserts that a numeric column adds up to an exact total. It is an aggregate rule: it looks at the column as a whole rather than at individual rows, which makes it the rule for reconciling a load against a control total.
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, the expected total, exact equality, NULL handling, filter behavior, and why coverage does not apply.
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Anomaly Reporting
The Shape Anomaly the check produces, what the numbers mean, and why there are no source records to inspect.
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Examples
Three production scenarios with sample data, the resulting anomaly message, and the SQL equivalent of what the check evaluates.
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Best Practices
Guidelines for control totals, scoping with a filter, and choosing between Sum and a per-row rule.
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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 a Sum check on a numeric field.
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Edit a Check
Step-by-step tutorial for changing the expected total or the filter on an existing check.
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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 exact totals, floating-point arithmetic, filters, and aggregate anomaly reporting.
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API
Payload shape and field notes for creating a Sum check programmatically.
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FAQ
Short answers to questions about the expected total, exact equality, NULLs, and anomaly reporting.