Analytics data is subject to change because Genesys Cloud runs a batch process known as pipeline, which is a nightly job that takes place overnight in all regions. The job reprocesses raw event data and inserts it back into their respective data stores.

The main purpose of the pipeline process is the following:

  • Make corrections to any minor real-time processing issues that can occur on the service. Real-time processing load is unpredictable, and if an event is overlooked, Genesys cannot rectify it in real-time. The batch processing that occurs nightly corrects these events.
  • Fault tolerance: In the unlikely event where a large-scale issue occurs on Genesys Cloud’s real-time processing stack, the pipeline operates independently to correct data.
  • Bug fix corrections: If a bug causes certain details or metric records to store incorrectly, these records can recalculate during the pipeline process.
  • Compliance: The process of deleting data that you must remove for compliance reasons, such as GDPR in Europe.
  • The rollout of new features, such as new, retroactive metrics.

The pipeline runs overnight and reprocesses data that is a minimum of 48 hours at the time that the job kicks off. However, the job can take longer due to the type of data being processed as well as other factors. If expected changes happen due to an issue in real time, the pipeline may begin processing that change after the conversation is at least three days old.

What should you do if you notice your data change?

  • Check the release notes for new features released that may cause new calculations or new data points to add to the platform.
  • Check the status page for any recent issues around real-time processing of analytics data.

Outside of any recent issues or releases, it is not expected behavior to see differences caused by pipeline rebuilding data nightly.

If you do notice changes, consider the following:

  1. What data changes took place?
  2. Is the change indicative of an improvement or a decline in the data under review?
  3. If further investigation is required, make sure to provide the following to Genesys Product Support:
    • ID information (queue ID, user IDs, conversation ID).
    • What data changes took place?
    • What was the expected outcome?
    • The data where the change took place; for example, the conversation details or user details data.

If you are unfamiliar with how to gather the analytics data, contact Genesys Product Support.