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The elementary.freshness_anomalies test monitors the freshness of your table over time, measuring the expected time between data updates.
Monitors the freshness of your table over time, as the expected time between data updates.

How it works

  1. Data is split into time buckets (daily by default, configurable with the time_bucket field).
  2. The maximum freshness value is computed per bucket for the last training_period (14 days by default).
  3. The test compares the freshness of each bucket within the detection period (last 2 days by default, controlled by the detection_period var) to the freshness of previous time buckets.
  4. If any anomalies are detected during the detection period, the test will fail.

Test configuration

Notes:
  • Required Configuration: timestamp_column
  • Default configuration*:* anomaly_direction: spike to alert only on delays.