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ETL with Azure Cookbook

You're reading from   ETL with Azure Cookbook Practical recipes for building modern ETL solutions to load and transform data from any source

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781800203310
Length 446 pages
Edition 1st Edition
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Authors (3):
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Christian Cote Christian Cote
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Christian Cote
Matija Lah Matija Lah
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Matija Lah
Madina Saitakhmetova Madina Saitakhmetova
Author Profile Icon Madina Saitakhmetova
Madina Saitakhmetova
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Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Getting Started with Azure and SSIS 2019 2. Chapter 2: Introducing ETL FREE CHAPTER 3. Chapter 3: Creating and Using SQL Server 2019 Big Data Clusters 4. Chapter 4: Azure Data Integration 5. Chapter 5: Extending SSIS with Custom Tasks and Transformations 6. Chapter 6: Azure Data Factory 7. Chapter 7: Azure Databricks 8. Chapter 8: SSIS Migration Strategies 9. Chapter 9: Profiling data in Azure 10. Chapter 10: Manage SSIS and Azure Data Factory with Biml 11. Other Books You May Enjoy

Chapter 7: Azure Databricks

Azure Databricks has become the de facto ETL tool in the cloud. It's a Unified Data Analytics Platform, meaning that it's more than an ETL tool. It can have access to many libraries that will allow a data engineer or a data scientist to work collaboratively and perform a wider task range; from ETL to machine learning and AI analysis.

Like Azure Data Factory, it's a Platform as a Service development and deployment environment. Unlike Data Factory, Databricks is not Azure specific. It is available on Microsoft Azure as well as the Amazon Web Services (AWS) platform. The main difference between Data Factory and Databricks from an ETL point of view is that Data Factory is a no-code environment. We basically use activities to do our ETL.

Databricks uses code and notebooks to achieve the same result. And as we will see later, it is the ETL tool when it comes to big data, whether it's measured in exabytes or petabytes. It is usually used...

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