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Azure Data Engineer Associate Certification Guide

You're reading from  Azure Data Engineer Associate Certification Guide

Product type Book
Published in Feb 2022
Publisher Packt
ISBN-13 9781801816069
Pages 574 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Newton Alex Newton Alex
Profile icon Newton Alex

Table of Contents (23) Chapters

Preface Part 1: Azure Basics
Chapter 1: Introducing Azure Basics Part 2: Data Storage
Chapter 2: Designing a Data Storage Structure Chapter 3: Designing a Partition Strategy Chapter 4: Designing the Serving Layer Chapter 5: Implementing Physical Data Storage Structures Chapter 6: Implementing Logical Data Structures Chapter 7: Implementing the Serving Layer Part 3: Design and Develop Data Processing (25-30%)
Chapter 8: Ingesting and Transforming Data Chapter 9: Designing and Developing a Batch Processing Solution Chapter 10: Designing and Developing a Stream Processing Solution Chapter 11: Managing Batches and Pipelines Part 4: Design and Implement Data Security (10-15%)
Chapter 12: Designing Security for Data Policies and Standards Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
Chapter 13: Monitoring Data Storage and Data Processing Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing Part 6: Practice Exercises
Chapter 15: Sample Questions with Solutions Other Books You May Enjoy

Implementing compression

In the previous chapters, we learned about the importance of data compression in data lakes. As the size of the data in data lakes grows, it becomes important that we store the data in a compressed format in order to save on cost. There are numerous ways in which we can implement compression in Azure. There are a lot of compression libraries available in the market and technically, all we need to do is write some scripts to call those libraries to compress data. But writing ad hoc scripts brings its own maintenance complexity, so let's look at some easy-to-maintain ways of implementing compression in Azure using Azure Synapse Pipelines. The same can be achieved using Azure Data Factory too. Azure Synapse Pipelines is just the same Azure Data Factory implementation within Synapse Analytics.

Compressing files using Synapse Pipelines or ADF

In the previous chapter, we learned about ADF. Like ADF, Synapse Pipelines can be used to create pipelines to...

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