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Azure Data Engineer Associate Certification Guide

You're reading from   Azure Data Engineer Associate Certification Guide A hands-on reference guide to developing your data engineering skills and preparing for the DP-203 exam

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Product type Paperback
Published in Feb 2022
Publisher Packt
ISBN-13 9781801816069
Length 574 pages
Edition 1st Edition
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Author (1):
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Newton Alex Newton Alex
Author Profile Icon Newton Alex
Newton Alex
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Azure Basics
2. Chapter 1: Introducing Azure Basics FREE CHAPTER 3. Part 2: Data Storage
4. Chapter 2: Designing a Data Storage Structure 5. Chapter 3: Designing a Partition Strategy 6. Chapter 4: Designing the Serving Layer 7. Chapter 5: Implementing Physical Data Storage Structures 8. Chapter 6: Implementing Logical Data Structures 9. Chapter 7: Implementing the Serving Layer 10. Part 3: Design and Develop Data Processing (25-30%)
11. Chapter 8: Ingesting and Transforming Data 12. Chapter 9: Designing and Developing a Batch Processing Solution 13. Chapter 10: Designing and Developing a Stream Processing Solution 14. Chapter 11: Managing Batches and Pipelines 15. Part 4: Design and Implement Data Security (10-15%)
16. Chapter 12: Designing Security for Data Policies and Standards 17. Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
18. Chapter 13: Monitoring Data Storage and Data Processing 19. Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing 20. Part 6: Practice Exercises
21. Chapter 15: Sample Questions with Solutions 22. Other Books You May Enjoy

Understanding the basics of partitioning

In the previous chapter, we briefly introduced the concept of partitioning as part of the Designing storage for efficient querying section. We explored storage-side partitioning concepts such as replicating data, reducing cross-partition operations such as joins, and eventual consistency to improve query performance. In this chapter, we will deep dive more systematically into both storage and analytical partitioning techniques. Let's start with the benefits of partitioning.

Benefits of partitioning

Partitioning has several benefits apart from just query performance. Let's take a look at a few important ones.

Improving performance

As we discussed in the previous chapter, partitioning helps improve the parallelization of queries by splitting massive monolithic data into smaller, easily consumable chunks.

Apart from parallelization, partitioning also improves performance via data pruning, another concept that we already...

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