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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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Toc

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

Extracting data from a Big Data Cluster

In this recipe, you are going to complete the development of an SSIS solution used to extract data from a database hosted on a Big Data Cluster instance in Azure and load it into a database hosted on the local SQL Server instance.

The purpose of this package is to reduce the size of the data that actually needs to be transferred from the external source into the line-of-business database, by restricting the remote source set to only contain data that does not yet exist in the local database.

In general, determining the delta hardly represents a task worthy of the capabilities available in Big Data Clusters or a typical case for using Spark; however, it does represent a very significant element in efficient data warehousing.

Getting ready

This recipe assumes that you have completed the preceding recipe in this chapter, entitled Loading data into a Big Data Cluster, and that the expected data is available in the dbo.NewPeople external...

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