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Azure Data Factory Cookbook

Azure Data Factory Cookbook

By : Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin, Xenia Ireton
4.9 (29)
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Azure Data Factory Cookbook

Azure Data Factory Cookbook

4.9 (29)
By: Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin, Xenia Ireton

Overview of this book

This new edition of the Azure Data Factory book, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF. There are updated and new recipes throughout the book based on developments happening in Azure Synapse, Deployment with Azure DevOps, and Azure Purview. The current edition also runs you through Fabric Data Factory, Data Explorer, and some industry-grade best practices with specific chapters on each. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. You'll familiarize yourself with the common errors that you may encounter while working with ADF and find out the solutions to them. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF with its latest advancements as the main ETL and orchestration tool for your data warehouse projects.
Table of Contents (15 chapters)
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13
Other Books You May Enjoy
14
Index

Creating an ADF pipeline using the Copy Data tool

We just reviewed how to create the ADF job using the UI. However, we can also use the Copy Data tool (CDT). The CDT allows us to load data into Azure storage faster. We don’t need to set up linked services, pipelines, and datasets as we did in the previous recipe. In other words, depending on your activity, you can use the ADF UI or the CDT. Usually, we will use the CDT for simple load operations, when we have lots of data files and we would like to ingest them into Data Lake as fast as possible.

Getting ready

In this recipe, we will use the CDT in order to do the same task of copying data from one folder to another.

How to do it...

We already created the ADF job with the UI. Let’s review the CDT:

  1. In the previous recipe, we created the Azure Blob storage instance and container. We will use the same file and the same container. However, we have to delete the file from the output location.
  2. ...
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