From the course: Advanced Microsoft Fabric Implementation and Governance
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Pipeline review and Azure compute
From the course: Advanced Microsoft Fabric Implementation and Governance
Pipeline review and Azure compute
- [Instructor] There are a number of different methods to transform data in Microsoft Fabric. There's Azure Data Factory dataflows, and those can provide a low-code method for transforming data. And there's Dataflow Gen2, and those provide the ability to use Power Query to modify the data. SQL notebooks can also be used to select and modify columns you want from data stored in lakehouses. And data can be completely transformed with Spark code in a notebook. Which one should you choose? In most cases, the method used should be part of a reusable pipeline, which means these are options within Azure Data Factory pipelines built to run repeatable processes. Azure Data Factory dataflows were originally created to replace local SIS transformations. It's a clicky, draggy method of development. One area that Microsoft has put a lot of energy into is the COPY command. This method is a really high-performing method of getting data. Technically, the COPY command is not considered a dataflows…
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