Could you please assist me? I am trying to understand how volume anomalies work and am attempting to recreate the issue. It was noticed that the test passes on some days and fails on others. I tried to calculate the row count using the

bucket_start

and

bucket_end

columns in the

elementary.data_monitoring_metrics

table, but this did not match the row count for that specific day in the table, which hindered my debugging efforts. Could you provide guidance on how volume anomalies work so that all related tests can pass consistently? This will help us understand why this is happening. Find below the metric_properties defined in same table

{
  "dimensions": null,
  "event_timestamp_column": null,
  "freshness_column": null,
  "time_bucket": {
    "count": 1,
    "period": "day"
  },
  "timestamp_column": "date_col",
  "where_expression": null
}