DP-700 - Ingest and Transform Data - Section 2.5
Choose between Dataflows Gen2, notebooks, KQL, and T-SQL for transforming batch data.
Choose among Dataflows Gen2 (Power Query), PySpark notebooks, T-SQL in a Warehouse, and KQL for transforming batch data. Weigh code-first flexibility against low-code maintainability, and recognise that KQL is best suited to log and telemetry data rather than relational batch workloads.
Dataflows Gen2 (Power Query) versus PySpark notebooksT-SQL in a WarehouseKQL for log and telemetry datacode-first versus low-code transformationskill set and maintainability trade-offs
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