Microsoft Azure Data Fundamentals DP-900 Practice Question

Streaming data is generated continuously and must be processed with minimal latency so that insights or actions can be taken almost immediately. Because each event is handled as it arrives, stream processing enables real-time dashboards, alerts, and automated reactions. Batch data, in contrast, is collected first-often in files or tables-and then processed on a schedule, so it tolerates longer delays. Therefore, only the option that emphasizes near real-time, event-by-event processing describes streaming data accurately. The other options reflect characteristics typical of batch workloads, such as relying on pre-stored files, accepting hours of latency, or focusing on high volume rather than velocity.