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

Product type Paperback

Published in Feb 2022

Publisher Packt

ISBN-13 9781801816069

Length 574 pages

Edition 1st Edition

Tools

Azure

Concepts

Big Data

Author (1):

Newton Alex

View More author details

Table of Contents (23) Chapters

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

Chapter 5: Implementing Physical Data Storage Structures

Hope you have had a good learning experience up till now. Let's continue our journey toward certification with more interesting topics in this chapter. Till the previous chapter, we have been focusing on the design aspects, but from now on, we will be focusing on the implementation details. We will learn how to implement the storage-level concepts that we learned in the previous chapters. Once you complete this chapter, you should be able to decide on and implement the following: what kind of data sharding is required, when to compress your data, how many partitions to create, what kind of data redundancy to maintain, and so on.

We will cover the following topics in this chapter: