Monitor quality rules - Precisely Data Integrity Suite

Manage rule run schedules directly from the rules list. Turn rule runs off or on to reduce processing costs while keeping access to historical scores and run details.

1. Go to Quality > Rules.
2. Open the context menu next to the associated rule.
3. Select Disable Scheduling to prevent the rule from running on the configured schedule. The scheduling status updates on the Rules page.
4. To turn scheduling on again, open the context menu and select Enable Scheduling. The rule resumes running on the configured schedule.

Quality scores evaluate dataset quality and reliability by using factors such as accuracy, completeness, consistency, timeliness, validity, uniqueness, and relevance. View scores for each field or dataset linked to a rule after successful run.

1. Go to Quality > Rules.
2. Select the specific rule name and go to the Rule Scores page.

   The page shows the following details:

   • Field or Dataset: Name of the field or dataset associated with the rule.
   • Score: Score generated for each associated field or dataset after rule evaluation.
   • Total records: Count of the total number of records considered for rule evaluation.
   • Evaluated: Count of total number of fields evaluated and considered during rule evaluation.
   • Passed: Count of the total number of records successfully evaluated. These represent the assets that satisfied the conditions set during rule evaluation.
   • Failed: Count of the total number of records that failed during rule evaluation. These represent assets that did not satisfy the conditions set during rule evaluation.
   • Last evaluated: Timestamp when the rule was last evaluated.
3. Select the specific asset to open the rules page and view the rules on which the scores are generated.

A rule definition specifies the conditions and parameters used to evaluate the rule. Review all configuration details, including dimensions, scoring bands, pass conditions, and expressions.

1. Go to Quality > Rules.
2. Select the specific rule name and go to the Rule Definition page.

   The page shows the following details about the rule definition:

   • Description: Description associated with the rule.
   • Dimension: Details on the dimension associated with the rule. For custom rules, the dimension corresponds to the value selected during rule creation.
   • Scoring bands: Predefined ranges or categories used to classify scores or performance metrics.
   • Show failed records sample: Indicates the failed records sample status for the respective rule.
   • Output failed records: Indicates whether failed records are persisted for SQL rule runs.
   • Scheduling: Details on whether scheduling is turned on or turned off for the respective rule.
   • Target Assets: Total number of assets considered for rule evaluation.
   • Evaluated rows filter: Conditions applied in the row filter for the rule.
   • Pass Conditions: Details on the pass conditions based on which the rule is evaluated. For default rules, the value is displayed as all fields.
   • Result Type: Expected result type. For default rules, the result type is metric evaluation.
   • Expression: Expression associated with the rule. For custom rules, the value corresponds to the pass conditions configured during rule creation.
3. Select the close button to return to the rules page.

The rule run status indicates the current state of rule runs for all rules in Quality. Track progress, identify errors, and troubleshoot rule run failures.

1. Go to Quality > Rules.
2. Select the run status associated with each rule to view further details.

   The details shown vary by run status value.

Failed record samples show records that failed rule evaluation. For SQL rules, failed records can also be persisted when failed records storage and failed-record output logging are turned on.

1. Go to Quality > Rules.
2. Select the associated rule name to view the details.

   This opens the Rule Scores page, which shows the following details:

   • Field or Dataset: Name of the associated field or dataset.
   • Score: Score generated after rule evaluation.
   • Total Records: Count of the total number of records considered for rule evaluation.
   • Passed: Count of the number of records that satisfied the defined condition for rule evaluation.
   • Failed: Count of the number of records that did not satisfy the defined condition and failed during rule evaluation.
   • Last evaluated: Timestamp when the rule was last evaluated.
3. Select the associated metric in the failed column to open the failed records page.

   The failed records page shows the following details:

   • Rule: Associated rule name for which the failed records are generated.
   • Pass condition: Defined condition for which the rule is evaluated.
   • Number of records: Number of sample records displayed out of the total number of records that failed rule evaluation.
   • Generated on: Timestamp when the sample was generated.
   • View rule definition: Provides details on the configured rule definition.
   • Delete Sample: Deletes the sample generated. On deleting the generated sample, the rules must run again to generate a new sample for the failed records.
   • The search bar provides an option to search for data in the associated columns in the generated sample.
   • The data in the column can be sorted to improve data organization and search efficiency.
4. Select the close button to return to the rules page.

Use failed records storage to persist failed records generated by SQL quality rule runs.

1. Go to Configuration > Quality > Data Storage.
2. Turn on Persist a log of all failed records for each rule run.
3. Under Outputs, enter an output name.
4. Choose the target option and target dataset.
5. Choose the connection associated with the target dataset.
6. Select Save.