Load Tracking Records FAQS

1. What is the purpose of loading tracking records?

•  Loading tracking records ensures that every insert and update operation on target tables is recorded in a separate tracking table. This is essential for compliance with regulatory requirements and maintaining an auditable history of data changes.

2. What should the tracking table contain?

•  The tracking table should contain:
• JOBID: Unique identifier for the ETL job.
• JOBNAME: Name of the ETL job.
• OPERATIONDATE: Timestamp when the operation occurred.
• OPERATIONTYPE: Type of operation (Insert or Update).
• All columns from the target table being tracked.

3. How does the tracking table get populated?

•  The tracking table is populated using an INSERT INTO SQL command. This command inserts the required tracking data, such as the job details, timestamp, operation type, and target table data, into the tracking table after each insert or update operation.

4. How is the operation type (Insert or Update) determined?

•  The operation type is determined by checking the value of a flag, such as IND_UPDATE. If IND_UPDATE = 'I', the operation is classified as an "Insert." If it's any other value (e.g., 'U' for Update), it is classified as an "Update."

5. Can the tracking table be created automatically if it doesn’t exist?

•  Yes, the tracking table can be created automatically by extending the Integration Knowledge Module (IKM). This customization allows you to check if the tracking table exists and create it if necessary, before loading the tracking data.

6. What if the tracking table already exists?

•  If the tracking table already exists, the system will simply insert the new tracking records for each operation (Insert or Update) as part of the ETL process. No additional creation logic is needed.

7. What happens if the insert command fails?

•  If the insert command fails, no tracking records will be inserted. It is important to handle errors properly by implementing error logging and retry mechanisms in the ETL process to ensure that tracking records are reliably inserted.

8. Can the tracking data be reviewed or audited later?

•  Yes, the tracking data can be reviewed or audited at any time. You can query the tracking tables to inspect the historical records, including the operation types, timestamps, and other metadata related to the insert or update operations.

9. How do I verify the accuracy of tracking data?

•  To verify the accuracy of tracking data:
• Ensure that JOBID and JOBNAME match the current ETL job.
• Check that OPERATIONDATE reflects the correct timestamp.
• Confirm that the OPERATIONTYPE is correctly labeled as Insert or Update.
• Validate that all data columns from the target table are correctly included in the tracking table.

10. Can I track operations for multiple target tables?

•  Yes, you can track operations for multiple target tables by creating a separate tracking table for each one. Each tracking table will contain the same structure and metadata as the target table, with an added suffix (e.g., _RGC).

11. How can I extend the tracking record loading process?

•  The tracking record loading process can be extended by adding additional metadata fields or including custom logic to handle special cases. For example, you might include the user who performed the operation or the source of the data for auditing purposes.

12. Can I load tracking records for deletes or other operations?

•  Yes, if required, the tracking process can be extended to include delete operations or other types of data changes. You can adjust the conditions or SQL logic to track additional operations beyond just inserts and updates.

13. Is it necessary to track every operation?

•  Tracking every operation is typically required for compliance with regulatory standards. However, depending on your organization's specific needs, you may decide to track only certain types of operations (such as Inserts and Updates) or specific columns in the target table.

14. What if the tracking table gets too large over time?

•  Over time, tracking tables may grow significantly. To manage this, you can implement archiving strategies to offload old records or set up partitioning for better performance and easier data management.