Release Notes › Announcements › Announcements for 14.1 › Initial Data Warehousing Job Prioritizes Events Captured in the Last Three Days

Initial Data Warehousing Job Prioritizes Events Captured in the Last Three Days

In the current release, the scope of the initial data warehousing job has changed. In previous releases, when this job ran on large CMS databases, CA DataMinder prioritized events captured in the last two months. Now the initial data warehousing job only prioritizes events captured in the last 3 days.

Background

CA DataMinder populates the data warehouse with event data as soon as possible after the BusinessObjects Integration feature or the iConsole dashboard have been installed or upgraded. Scheduled jobs to populate the data warehouse run automatically. In the current release, on CMSs with over 100,000 events, CA DataMinder processes events captured in the last 3 days as soon as possible after installation or upgrade. CA DataMinder then processes events older than 3 days by running daily off-peak data warehousing jobs.

In previous releases, CA DataMinder processed events captured in the last 2 months as soon as possible after installation or upgrade.

However, in all cases you can change the data warehousing job parameters and the job frequency.

Who Does This Change Affect?

This change only affects existing CA DataMinder customers who need to truncate and partition the data warehouse and who have a CMS with over 100,000 events. These customers may notice that the data warehouse takes longer to become fully populated after truncating and partitioning the data warehouse.

Note: You typically need to truncate and partition the data warehouse if you regularly purge events from you CMS database, it is likely that your data warehouse contains any events that no longer exist on the CMS. Specifically, the event participant details for these events no longer exists. Therefore these participant details cannot be processed into the Event Participant Fact table in the data warehouse. In this situation, we recommend that you truncate and repopulate the entire data warehouse to avoid discrepancies in report results.