Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You create an Eventstream in Microsoft Fabric that ingests telemetry from an Azure IoT Hub into a Real-Time Analytics KQL database. The analytics team needs a query that will drive a live Power BI report and must meet these requirements:
Show the number of messages per device over the most recent one-minute interval.
Refresh the metric every 10 seconds without double-counting events that fall into more than one refresh cycle.
Tolerate events that arrive up to 30 seconds after their original event time.
You plan to define a continuous query on the Messages table that contains the columns DeviceId, EnqueuedTime (event time), and Payload.
Which KQL construct should you use in the summarize clause to meet all the requirements?
A hopping window generates overlapping windows that advance by a fixed hop size, so each new result set (refreshed every 10 seconds) covers the last 60 seconds of data without re-counting events already aggregated in earlier hops. By specifying hoppingwindow(EnqueuedTime, 1m, 10s, 30s) you additionally instruct the engine to hold the window open for 30 seconds, ensuring that late-arriving events are still included. Tumbling and sliding windows do not produce the overlapping 10-second refresh cadence that the report expects, and using bin() alone cannot both refresh every 10 seconds and protect against double counting or late arrival.
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Microsoft Fabric Data Engineer Associate DP-700
Ingest and transform data
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