One of the key components of the Azure Cloud platform is the ability to store and process large amounts of data. Azure Data Flow Transformations can be used to ingest and transform data.
In this course, you'll learn about the types of Azure Data Flow transformations that are available. You'll explore how to transform, split, and flatten data, as well as handle duplicate data, using Azure Data Mapping Data Flows. Next, you'll examine the types of expression functions available in Azure Data Flow and how to perform error handling for data rows that would truncate data. Finally, you'll learn how to transform and use derived columns to normalize data values, and how to ingest and transform data using Azure Spark and Scala.
This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
Learning Objectives
{"discover the key concepts covered in this course"}