From the course: Data Integration and API Development for AI Applications
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ETL with Fabric dataflows
From the course: Data Integration and API Development for AI Applications
ETL with Fabric dataflows
In this demo, we'll continue working within the LoonyLakehouse that we had created in our Microsoft Fabric Workspace. This time, when we ingest data, we'll do so using a simple ETL pipeline. Fabric includes a feature called Dataflow, which is a low-code ETL Extract, Transform, low tool that lets users ingest clean and transformed data using Power Query. I'll create a new Dataflow and we'll use this to read our Adidas sales data from our Azure Blob Storage, transform it, and then store it within our LoonyLakehouse. I'm going to call this Dataflow IngestDataFromADLS. Go ahead and hit Create. This opens up Microsoft's Power Query Editor. Power Query is a data transformation and preparation tool that lets users connect to various data sources, clean, reshape, and combine data using a visual step-by-step interface. You don't need to write any code. Click on Get Data From Another Source, and we'll connect to our Azure Blob Storage account. Search for Azure here, and the option that we want…
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