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Azure Data Factory Cookbook

You're reading from   Azure Data Factory Cookbook Build ETL, Hybrid ETL, and ELT pipelines using ADF, Synapse Analytics, Fabric and Databricks

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781803246598
Length 532 pages
Edition 2nd Edition
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Authors (4):
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Tonya Chernyshova Tonya Chernyshova
Author Profile Icon Tonya Chernyshova
Tonya Chernyshova
Xenia Ireton Xenia Ireton
Author Profile Icon Xenia Ireton
Xenia Ireton
Dmitry Foshin Dmitry Foshin
Author Profile Icon Dmitry Foshin
Dmitry Foshin
Dmitry Anoshin Dmitry Anoshin
Author Profile Icon Dmitry Anoshin
Dmitry Anoshin
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Toc

Table of Contents (15) Chapters Close

Preface 1. Getting Started with ADF 2. Orchestration and Control Flow FREE CHAPTER 3. Setting Up Synapse Analytics 4. Working with Data Lake and Spark Pools 5. Working with Big Data and Databricks 6. Data Migration – Azure Data Factory and Other Cloud Services 7. Extending Azure Data Factory with Logic Apps and Azure Functions 8. Microsoft Fabric and Power BI, Azure ML, and Cognitive Services 9. Managing Deployment Processes with Azure DevOps 10. Monitoring and Troubleshooting Data Pipelines 11. Working with Azure Data Explorer 12. The Best Practices of Working with ADF 13. Other Books You May Enjoy
14. Index

Managing Deployment Processes with Azure DevOps

Azure DevOps offers a comprehensive set of development collaboration, continuous integration, and continuous delivery tools. With Azure Repos, you can collaborate on code development using free public and private Git repositories, pull requests, and code reviews. Meanwhile, Azure Pipelines enables you to implement a streamlined build, test, and development pipeline for any application.

In this chapter, we will delve into setting up CI and CD for data analytics solutions in Azure Data Factory (ADF) using Azure DevOps.

Continuous Integration (CI) is a practice where code changes are regularly integrated into a shared repository, ensuring that each change is automatically built, tested, and validated.

Continuous Deployment (CD) is the automatic deployment of changes to production or staging environments after they pass CI tests.

By implementing CI/CD in the context of data analytics, you can streamline the development process...

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