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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

Summary

With that, we have come to the end of our second chapter. We explored the various data lake designs in detail and learned good practices for designing one. You should now be comfortable answering questions related to data lake architectures and the storage, compute, and other technologies involved in creating a data lake. You should also be familiar with common file formats such as Avro, Parquet, and ORC and know when to choose which file formats. We also explored different optimization techniques such as data pruning, partitioning, caching, indexing, and more. We also learned about folder structures, data distribution, and finally, designing a data life cycle by using policies to archive or delete data. This covers the syllabus for DP-203 exam, Design a Data Storage Structure chapter. We will be reinforcing the learnings from this chapter via implementation details and tips in the following chapters.

Let's explore the concept of partitioning in more detail in the next...

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