Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You need to design a loading pattern that writes high-throughput IoT telemetry from an eventstream into a Microsoft Fabric Lakehouse so that downstream analytics can query the data in near real time without repeatedly managing schema evolution or file management logic. Which target should you configure as the sink for the eventstream?
A mirrored table sourced from an external SQL database
A streaming table created in the destination Lakehouse
A standard warehouse table in the same workspace
A Lakehouse folder added as a shortcut to external ADLS Gen2 storage
Streaming tables in a Fabric Lakehouse are optimized for continuous append-only writes coming from eventstreams. They automatically store data in Delta Lake format, manage file sizes, and handle evolving schemas without requiring manual compaction or ALTER TABLE statements. Warehouse tables expect batch loads, and shortcut folders simply reference external data rather than ingest it. Mirroring connects to an external database and is unrelated to eventstream output.
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What is a streaming table in Microsoft Fabric Lakehouse?
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Microsoft Fabric Data Engineer Associate DP-700
Ingest and transform data
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