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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

Copying data from Google Cloud Storage to Azure Data Lake

In this recipe, we will use the in-built Microsoft connectors to copy the data from Google Cloud Storage to an Azure Storage account. You will learn how to configure the Google Storage account and grant permissions to allow your data factory to connect and import the files.

Getting ready

For this recipe, you will need to have a Google Cloud account and at least one Google Storage bucket:

  1. To set up a free Google Cloud account and create your first project, refer to the Technical requirements section. Once your project is set up, go to your dashboard and copy your project ID.
  2. Then, go to the Google Storage browser. It can be accessed at this URL: https://console.cloud.google.com/storage/browser?<your-project-id>. Be sure to replace the your-project-id field in the URL with the correct value.
  3. In the Google Storage browser, create a new bucket. Once the bucket is created, upload the CSV files from...
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