Stuck on pulling granular schedule adherence metrics for our Chicago-based support team into a custom Power BI dashboard. We are leveraging the Genesys Cloud Analytics API to fetch real-time and historical performance data, specifically focusing on the wfm:schedule:adherence metric. The issue arises when querying for specific date ranges that include recent shift swaps published via the WFM self-service portal. When I execute a GET request to /api/v2/analytics/wfm/schedules/query with a filter for scheduleStatus=PUBLISHED, the response payload consistently omits agents who have recently executed a shift trade. The API returns a 200 OK status, but the items array lacks the shiftId references for those specific agents, resulting in a NULL value for their adherence calculations in the downstream report. I have verified that the schedule is fully published and visible in the WFM UI, and the agents’ statuses are correctly reflected as ON_BREAK or AVAILABLE in the real-time dashboard. The discrepancy seems to stem from a latency or caching issue within the Analytics API, as the data appears correctly if I wait more than 15 minutes after the swap is approved. We are using the Python 3.10 SDK with version 1.28.4 for these queries. Is there a specific parameter to force a cache refresh or a dedicated endpoint to fetch post-swap schedule data immediately? Our weekly reporting cycle depends on this data being accurate within hours of schedule publication, not days. The current workaround involves manually exporting CSVs from the WFM UI, which defeats the purpose of our automated reporting pipeline. I have checked the API documentation for wfm:schedule:export but it seems designed for bulk historical data rather than real-time adherence tracking. Any insights on how to bridge this gap between the WFM transactional database and the analytical data warehouse would be incredibly helpful. We need a reliable method to ensure that shift swaps are reflected in our adherence metrics without significant delay.