Mapping Data Flows in Azure Data Factory: Building Scalable ETL Projects in the Microsoft Cloud

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022

M. KromerMapping Data Flows in Azure Data Factoryhttps://doi.org/10.1007/978-1-4842-8612-8_6

6. Slowly Changing Dimensions

Mark Kromer¹  

(1)

SNOHOMISH, WA, USA

 

So far in this book, we’ve covered the basics of ADF’s pipelines and Mapping Data Flows . We’ve walked through common pipeline patterns for cloud-first ETL jobs with ADF and the development and design process. Now let’s shift our focus to diving deep into Mapping Data Flows by exploring a few common patterns that you’ll use in ADF. In this chapter, we’ll talk about the slowly changing dimension scenario. A few of the data flow constructs that we’ll use here include derived column, surrogate key, union, ...