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Min count

Data quality rule that verifies if a data quality check reading is greater or equal a minimum value.

Parameters

This rule has one parameter that should be configured for each alert :

  • low:
    rule threshold for a low severity (1) alert
    • min_value: float
      minimum accepted value for the actual_value returned by the sensor (inclusive)
  • medium:
    rule threshold for a medium severity (2) alert
    • min_value: float
      minimum accepted value for the actual_value returned by the sensor (inclusive)
  • high:
    rule threshold for a high severity (3) alert
    • min_value: float
      minimum accepted value for the actual_value returned by the sensor (inclusive)

Example

The following example shows how to implement min_count rule for a check.

The assigned severity depends on sensor result (see YAML configuration below):

  • result >= 90.0, the check is passed: valid result
  • 90.0 > result >= 80.0 the severity is low (1)
  • 80.0 > result >= 70.0 the severity is medium (2)
  • 70.0 > result, the severity is high (3)
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# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  target:
    schema_name: test_data
    table_name: string_dates
  time_series: null
  columns:
    dates:
      type_snapshot:
        column_type: STRING
        nullable: true
      checks:
        validity:
          date_type_percent:
            rules:
              min_count:
                low:
                  min_value: 90.0
                medium:
                  min_value: 80.0
                high:
                  min_value: 70.0