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Volume

Monitor number of records, non-NULL values, duplicates, unique values etc.

Configuration

StepRequiredParameters / Options
Validator typeVolume-
ConfigMetricCount
Percentage
Duplicate count
Duplicate percentage
Unique count
Unique percentage
ConfigBackfillInitialize with backfill (checkbox)
Source configFieldNo field (use record) (default)

Or

List of source fields
Source configSegmentation1. Select a configured Segmentation

Or

2. Unsegmented (default)
Source configWindowSelect a configured Window
Source configFilterNo filter (default)
Boolean
Enum
Null (*1)
String
Threshold filter
ThresholdThreshold typeFixed threshold
Dynamic threshold
Threshold✅(*2)OperatorLess than
Less than or equal
Equal
Not equal
Greater than
Greater than or equal
Threshold✅(*2)ValueNumeric value to validate threshold on
Threshold✅(*3)SensitivityEnter a numeric value
Threshold✅(*3)Decision bounds typeUpper
Lower
Upper and lower (default)

*1 Only applicable for nullable columns.

*2 Only applicable for Fixed thresholds.

*3 Only applicable for Dynamic thresholds.

Configuration details

Field selection

For metrics Count and Percentage you can pick No field (use record) to count entire records. You can also pick a specific field to count non-NULL values in that field.

**Volume** Validator Configuration Wizard - Single field in Source config.

Volume Validator Configuration Wizard - Single field in Source config.

For metrics Duplicates count, Duplicates percentage, Unique count and Unique percentage you have to specify one or several fields. Specifying several fields means field values are concatenated before being counted, which is, for example, useful when validating uniqueness of composite keys.

Note: For duplicate- and unique metrics, Validio counts NULL values as any other value, unless you apply a NULL filter.

**Volume** Validator Configuration Wizard - Multiple fields in Source config.

Volume Validator Configuration Wizard - Multiple fields in Source config.

Sensitivity

Higher sensitivity means that the accepted range of values is narrower, which identifies more anomalies. Conversely, lower sensitivity values imply a wider range of accepted values, which identifies fewer anomalies.