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Introduction to the Volumetric Check

The Volumetric check asserts that a table or file holds the number of rows you expect. It compares the row count against a fixed range, or against the count from an earlier day, and reports a Shape Anomaly when the volume falls outside the limits you set. It answers how much data arrived. Its counterpart, Freshness, answers when data last arrived.

This section is the complete guide to the check. The Deep Dive covers the definition, properties, and evaluation semantics, details each comparison, 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

  • How It Works

    The complete reference: definition, when the check is evaluated, the properties, the history it needs, and AI Managed Volumetric checks.

    How It Works

  • Comparisons

    What Absolute Value, Absolute Change, and Percentage Change measure, and what each one compares against.

    Comparisons

  • Anomaly Reporting

    What the Shape Anomaly reports, how to read the numbers in the message, and why there is nothing to report per row.

    Anomaly Reporting

  • Examples

    Three production scenarios: a load that adds no rows, a weekly growth band, and a fixed volume range.

    Examples

  • Best Practices

    Guidelines for choosing the comparison and Measurement Period, scheduling the Scan, and working with AI Managed checks.

    Best Practices

  • Permissions

    The team permission each action needs: view, create, edit, archive, restore, and delete.

    Permissions

  • Create a Check

    Step-by-step tutorial for creating a Volumetric check on a table or file.

    Create a Check

  • Edit a Check

    Step-by-step tutorial for changing the limits, the Measurement Period, or the comparison of a check that has not run yet.

    Edit a Check

  • Delete a Check

    Step-by-step tutorial for archiving a check and deleting it permanently.

    Delete a Check

  • Troubleshooting

    Common problems: no anomaly despite a missed load, a check that is never asserted, and a comparison that cannot be changed.

    Troubleshooting

  • API

    Payload shape and field notes for creating a Volumetric check programmatically.

    API

  • FAQ

    Short answers to questions about when the check runs, the history it needs, and AI Managed Volumetric checks.

    FAQ