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Azure Data Factory Cookbook

You're reading from   Azure Data Factory Cookbook Build and manage ETL and ELT pipelines with Microsoft Azure's serverless data integration service

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Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781800565296
Length 382 pages
Edition 1st Edition
Tools
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Authors (4):
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Dmitry Anoshin Dmitry Anoshin
Author Profile Icon Dmitry Anoshin
Dmitry Anoshin
Roman Storchak Roman Storchak
Author Profile Icon Roman Storchak
Roman Storchak
Xenia Ireton Xenia Ireton
Author Profile Icon Xenia Ireton
Xenia Ireton
Dmitry Foshin Dmitry Foshin
Author Profile Icon Dmitry Foshin
Dmitry Foshin
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Toc

Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Getting Started with ADF 2. Chapter 2: Orchestration and Control Flow FREE CHAPTER 3. Chapter 3: Setting Up a Cloud Data Warehouse 4. Chapter 4: Working with Azure Data Lake 5. Chapter 5: Working with Big Data – HDInsight and Databricks 6. Chapter 6: Integration with MS SSIS 7. Chapter 7: Data Migration – Azure Data Factory and Other Cloud Services 8. Chapter 8: Working with Azure Services Integration 9. Chapter 9: Managing Deployment Processes with Azure DevOps 10. Chapter 10: Monitoring and Troubleshooting Data Pipelines 11. Other Books You May Enjoy

Creating an ADF pipeline by using the Copy Data tool

We just reviewed how to create the ADF job using 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 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. Go to Azure Storage...
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