Rule Executions

The Rule Executions tab, accessible for every data quality rule, serves as a comprehensive resource for users seeking insights into the execution history of their Data Quality Rules. It offers a high-level overview of total associated objects, execution time details, and user-related information for each rule execution. Users can track the progression of Data Quality Rules executions, understand outcomes, and delve into crucial details such as execution logs, number of objects passed, failed, undetermined, execution failed, result execution ID, result, overall object count, execution timing, and the user responsible for each execution.

• Logs: Clicking on the log eye icon reveals the job logs associated with a specific Rule Execution Id. This option consolidates all essential execution details at the Data Quality Rule (DQR) level, eliminating the need for users to navigate to the Jobs module to track job logs for each rule execution.

• Select Date: Aids in searching job logs between the provided date and timestamp.

• Search Job Logs: Facilitates searching content based on the provided keyword.

• Filter Options: Assists in filtering job logs based on their type, i.e., Info, Warning, and Error.

• Refresh: Allows refreshing applied filters, search results, and displaying all job logs for the particular Job Id.

• Download: Helps download the job log.

• Rule Execution ID: Each Data Quality Rule is assigned a unique Rule Execution ID, offering users a distinct identifier to recognize and distinguish the execution results of a specific data quality rule. This ID helps in understanding the rule's status, reviewing generated statistics, and gaining insights into the outcomes for associated objects during that particular execution. By providing this unique identifier, clarity is enhanced, and effective tracking of the rule's performance and associated data quality metrics is facilitated.

• DQ Rule Report: When a user accesses the Rule Execution ID, it opens up a DQR Report, offering in-depth insights into a specific rule execution, covering all execution details of associated objects within that execution.

• The DQ Rule Report is structured into two sections.

  • The first section, Rule Summary, encompasses contextual information such as Rule Name, Purpose, Rule ID, Rule Execution ID, Success Criteria, configuration settings, timestamps of execution (Start time, End Time, Run By, and Duration), statistics of associated objects (Passed Objects, Failed Objects, Undetermined Objects, Execution Failed Objects, Total Objects), and the execution status (Result).

  • The second section, DQ Rules Execution Details, provides information for associated objects, presenting contextual details, results, and statistics recorded post-rule execution. Users can freely select different objects and compare results within this section, facilitating a detailed analysis of the rule's impact on individual associated objects.

  • Result: This column presents essential information capturing the Execution Result of the DQR per execution. Users can utilize the filter option to sort DQR based on their execution results. The following options are available under this column:

• Failed: Indicates that the DQR encountered failure during its execution.

• Passed: Denotes successful completion of DQR execution without issues.

• Execution Failed: Indicates failure due to connection issues with associated objects or errors in Data Quality Function queries.

• Undetermined: Signifies an inconclusive determination of the DQR execution result. Additionally, an eye icon is provided, offering a message based on the status and a summary including Input, Success Criteria, Passed Objects, Failed Objects, Number of Service Requests Created, Number of Failed Values sent to Remediation Center, and Downstream Objects Cautioned.

• Passed Objects Count: This column displays the count of Associated Objects that were successfully executed during the rule execution.

• Failed Objects Count: This column lists the count of Associated Objects that encountered failures during the rule execution.

• Undetermined Objects Count: This column indicates the count of Associated Objects that were undetermined during the rule execution.

• Execution Failed Objects Count: This column displays the count of Associated Objects that encountered execution failures during the rule execution.

• Total Objects Count: This column shows the count of the total Associated Objects added to the rule.

• Start Time: This column showcases the timestamp when the DQR execution was initiated.

• End Time: This column presents the timestamp indicating when the DQR execution was successfully completed.

• Duration: This column illustrates the duration taken by the DQR to complete its execution.

• Run By: This column exhibits the username of the individual who initiated the execution of the DQR.

Object Execution Results

This tab serves as a source of detailed information, providing insights into the execution details at the object level. It offers a comprehensive view of how each associated object has performed in each rule execution.

The important columns under this tab include:

• Rule Execution ID: Each Data Quality Rule (DQR) is assigned a unique Rule Execution ID, offering users a distinct identifier to discern and differentiate the execution results of a specific data quality rule.

• Object Execution ID: Each object associated with a data quality rule is allocated a unique Object ID for every execution. To understand the relationship between Object Execution ID and Rule Execution ID, consider the following example:

Data Quality Rule Name	Email Validation
No. of Associated Objects	3
Name of Associated Objects	Column 1, Column 2, Column 3
No. of Rule Executions	4
Rule Execution Id	Object Execution Id	Object Name
20	1	Column 1
20	1	Column 2
20	1	Column 3
21	2	Column 1
21	2	Column 2
21	2	Column 3
22	3	Column 1
22	3	Column 2
22	3	Column 3
23	4	Column 1
23	4	Column 2
23	4	Column 3

• In the provided table, the Email Validation Rule undergoes four executions, and for each Rule Execution, all three associated table columns share a common Object Execution ID. This correlation between Rule and Object Execution IDs facilitates linking the Data Quality Rule to its associated objects, enabling users to identify and monitor the execution details of the DQR alongside its objects.

• The following columns offer contextual information about the associated data objects when a Data Quality Rule is created for table columns. These columns are listed on the Object Execution Results tab.

• Database: This column showcases the database. Users can utilize the filter option to narrow down the respective databases for easier navigation and analysis.

• Schema: This column exhibits the schema. Users can utilize the filter option to narrow down and focus on specific schemas for more streamlined navigation and analysis.

• Table: This column shows the table name. Users can use the filter option to narrow down the respective tables for easier navigation and analysis.

• File: This column presents the file name. Users can leverage the filter option to narrow down the respective files for easier navigation and analysis.

• Column: This column indicates the column name to which the selected table/file column belongs. Users can use the filter option to refine the view and concentrate on the respective schemas for enhanced navigation and analysis.

• Failed Values: This column records the failed values identified after the rule execution. It is specifically supported for Table Column and File Column functions where the calculation of failed values is applicable. By clicking on the eye icon, users can view the entire list of failed values in that column.

• Passed Row Count: This column indicates the total number of passed rows present in the associated Table Column. This result is retrieved from the source system and is also displayed as a percentage.

• Failed Row Count: This column indicates the total number of failed rows present in the associated Table Column. This result is retrieved from the source system and is also displayed as a percentage.

• Total Row Count: This column indicates the total number of rows present in the associated Table Column. This result is retrieved from the source system and is also displayed as a percentage.

• Result Value: This column displays the calculated result value for a specific record after the rule execution.

For example: Data Quality Rule Name: Checking Valid Email Format Purpose: To evaluate the count of valid email values within a specified column. The rule checks whether the email values conform to the standard pattern of “[email protected]”

After the rule execution following statistics have been generated:

Total Row Count	Passed Row Count	Failed Row Count	Success Criteria	Result Value
50	19 (38%)	31 (62%)	Result value count should be equal to 100	19

• In the provided example, out of a total of 50 rows in a table column, if 19 rows meet the criteria for records in the desired email format, then the Result Value will be 19.

• Result: This column presents essential information capturing the Execution Result of the DQR per execution. Users can utilize the filter option to sort DQR based on their execution results.

• The following options are available under this column:

• Failed: Indicates that the DQR encountered failure during its execution.

• Passed: Denotes successful completion of DQR execution without issues.

• Execution Failed: Indicates failure due to connection issues with associated objects or errors in Data Quality Function queries.

• Undetermined: Signifies an inconclusive determination of the DQR execution result.

• Additionally, an eye icon provides a message based on the status and a summary including Result Value, Input, Success Criteria, Maximum Failed Values for Remediation, Service Request ID, Failed Values sent to Remediation Center, and Downstream Objects Cautioned.

• Run On: This column provides users with the timestamp indicating when the associated data object was last executed. Users can sort the entries by timestamp to view either the newest or oldest executions.