Processing Slowly Changing Dimensions with ADF Data Flows

Do you want to learn how to use slowly changing dimensions with Azure Data Factory? In a recent webinar, Bob Rubocki gives an overview of Azure Data Factory Data Flows and loading dimensions in data warehouses.

Bob will start with discussing what data flows are in Data Factory and how they work, as well as setting up Type 1 and Type 2 scenarios. This will set you up with an understanding for when he goes into Type 1 and Type 2 dimension processing.

Azure Data Factory Data Flows, otherwise referred to as Mapping Data Flows, is a visual data transformation tool within ADF. Prior to Data Flows the Copy Data Activity allowed us to move data from one place to another, but it was very limited for transformations or building calculations on the fly. Data Flows allows us more of that transformation of our data.

Bob will do a quick review of some of these transformations that we have available with Data Flows and many of these are included in his demo. From there, you’ll learn about the typical data warehouse load patterns and the differences between Type 1 and Type 2 patterns.

The remainder of this webinar is spent on a demo of using dimension load patterns with Azure Data Factory Data Flows. So, if you’d like to learn about using slowly changing dimensions in ADF, this webinar is for you. You can watch the complete webinar below. To see the slides from the presentation, click here.

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