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Field stats monitors automatically track key statistical properties of one or more fields in a table and learn a time-series pattern for each metric. These monitors help you detect unexpected changes in distribution, null rates, or value ranges without writing any SQL. Examples of what you can detect with field stats monitors:
  • Sudden spikes in null or empty values after a pipeline change
  • Drops in the number of unique IDs, indicating upstream duplication issues
  • Unusual shifts in a numeric metric such as fare amount, order value, lead time, etc.
  • Outliers in mean, max, or standard deviation that may indicate data corruption

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Metrics tracked automatically

Each selected field will automatically generate a time-series for the following metrics (depending on data type):

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Setting up a field stats monitor

  1. Navigate to the table where you want to create the monitor and click Add Monitor title
  2. Select Field stats and choose the fields you want to monitor
    You can monitor one or multiple fields at once.
  3. Configure time partitioning. A time-series will be learned per metric per field, using the timestamp column you select. title
  4. Set sensitivity, and severity (optional) title
Once confirmed, the monitor will appear under the table and on the Health page
Field stats monitors bootstrap the past 30 days of history, then only query new partitions going forward to reduce cost. Anomaly detection begins immediately after setup.

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Resetting a monitor

If you modify historical data and want to re-learn the 30-day baseline, open the monitor, go to Settings, and click Reset monitor. This action is not reversible — only reset if you are certain the historical values have changed.