Microsoft Azure Data Fundamentals DP-900 Practice Question

Analytical workloads are designed to examine large volumes of historical data, typically loaded in batches, to discover trends or generate aggregated reports. They are read-heavy, involve complex queries such as joins and aggregations, and can tolerate higher query latency because results are not required in real time. In contrast, transactional workloads focus on many small, fast insert, update, or delete operations that demand low-latency responses and strict consistency for current operational data. Therefore, the description that best matches the overnight reporting workload is the option describing complex aggregations over large historical datasets with tolerance for higher latency; the other options describe characteristics of transactional (operational) systems.