Comprehensive and Detailed Explanation From Exact Extract:

Pega’s integration capabilities, as outlined in Pega Academy’sIntegration Missionand thePega Certified Lead System Architect Study Guide, provide multiple approaches for sending data to external systems like a data warehouse via REST APIs. The solution must balance efficiency, scalability, and near real-time requirements for both historical and in-flight case data.

Option A (Incorrect): Using data flows to source data and synchronously post to the data warehouse is inefficient for near real-time reporting. Synchronous REST calls can introduce latency and performance issues, especially for large datasets. Pega recommends asynchronous processing for integration tasks to ensure scalability, as noted in theIntegrationmodule.

Option B (Correct): Using an extract rule to process already-resolved cases is ideal for historical data. Extract rules (part of Pega’s Business Intelligence Exchange, BIX) are designed to efficiently export large volumes of data to external systems like data warehouses. For in-flight cases, posting data via REST on case resolution ensures near real-time updates. This approach aligns with Pega’s best practices for data extraction and integration, per theBIX Configurationmodule.

Option C (Correct): Data flows sourcing data via a dataset and outputting to a queue processor for REST posting is a scalable, asynchronous solution for historical data. Queue processors handle high volumes efficiently, and reusing the same queue processor for in-flight case resolutions ensures consistency and near real-time updates. This is supported by theData Flow and Queue Processorsections in Pega Community.

Option D (Incorrect): A one-time utility for historical data is not sustainable for ongoing reporting needs, as it lacks automation. Additionally, synchronous posting for in-flight cases risks performance bottlenecks, which contradicts Pega’s asynchronous integration recommendations, per theIntegration Mission.