The Rule tab of the profiling area shows all validation constraints and data quality rules used by the data model. A validation constraint represents each defined parameter of an attribute: the type, the minimum/maximum values, the precision, the validation pattern, the date, time, and if empty values are allowed. When a parameter is defined, each value of the attribute is validated against this constraint. For example, minimum value is 3.
This tab allows you to know the number and percentage of:
- Valid, empty, and invalid values for each validation constraint. The empty values are taken into account if Allow empty values is enabled for the attribute. When the setting is disabled, if the constraint is fulfilled, the value is valid. Otherwise, the value is invalid.
- Valid, non-applicable, and invalid values for each data quality rule. The non-applicable values are the values that do not fulfill the condition of the data quality rule.
Procedure
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Click a color in one of the quality bars.
Color Constraint Data quality rule Red The values are invalid. They do not match the attribute type or are outside the defined range. The values are invalid. They fulfill the condition but not the validation expression or the rule cannot be executed on those values. For example, if the rule must compare a string with a number. For more information on the errors, click the red vertical bar next to the value. Gray The fields are empty. - Light green - The values are not applicable. They do not fulfill the condition and no alternative validation expression has been defined. Green The values are valid. They match the attribute type and are in the defined range. The values are valid. They fulfill all rule statements. The tasks are filtered by this color.
When a rule contains errors, it no longer applies to the tasks and a red bar is displayed. Click it for more information.