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You are implementing a medallion architecture in a Fabric lakehouse. Raw data lands in the Bronze layer as CSV files. You need to clean, deduplicate, and convert the data to Delta tables in the Silver layer using PySpark. Which Fabric item should you use?
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Alex
For Bronze-to-Silver transformations requiring PySpark, a Spark notebook is the correct choice. Notebooks provide full programmatic control for cleaning, deduplication, type casting, schema enforcement, and writing Delta tables. Why not the others? A SQL stored procedure operates in the Warehouse, not the Lakehouse. Dataflow Gen2 is low-code and doesn't natively support PySpark. A KQL queryset is for Real-Time Intelligence, not lakehouse ETL. In Fabric's medallion architecture, notebooks are the primary tool for complex transformations between layers. Ref: learn.microsoft.com/fabric/onelake/onelake-medallion-lakehouse-architecture
Sourcelearn.microsoft.com
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