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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

Migrating data from Google BigQuery to Azure Synapse

In this recipe, we will import a public dataset, github_repo.files, from Google BigQuery into Azure Synapse – formerly Azure Data Warehouse. We will create a SQL data pool, create the table to store our imported data, and configure the pipeline to migrate data from a public dataset hosted at Google BigQuery.

Getting ready

To complete this recipe, you will need a Google Cloud project with the BigQuery API enabled. Refer to the Getting ready section in the previous recipe for instructions on how to set those up and obtain your Project ID, Client ID, Client Secret, and Refresh Token fields.

You will also need an instance of an Azure Synapse SQL pool to import the data. Refer to the chapter on Azure Synapse on how to create and configure a SQL pool. Have the login credentials for this SQL pool to hand.

You will also need to create a table in your database to store the data we import. Download the script to create...

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