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Azure Data Engineer Associate Certification Guide

You're reading from   Azure Data Engineer Associate Certification Guide Ace the DP-203 exam with advanced data engineering skills

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781805124689
Length 548 pages
Edition 2nd Edition
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Authors (3):
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Newton Alex Newton Alex
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Newton Alex
Giacinto Palmieri Giacinto Palmieri
Author Profile Icon Giacinto Palmieri
Giacinto Palmieri
Mr. Surendra Mettapalli Mr. Surendra Mettapalli
Author Profile Icon Mr. Surendra Mettapalli
Mr. Surendra Mettapalli
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Azure Basics FREE CHAPTER
2. Chapter 1: Introducing Azure Basics 3. Part 2: Data Storage
4. Chapter 2: Implementing a Partition Strategy 5. Chapter 3: Designing and Implementing the Data Exploration Layer 6. Part 3:Data Processing
7. Chapter 4: Ingesting and Transforming Data 8. Chapter 5: Developing a Batch Processing Solution 9. Chapter 6: Developing a Stream Processing Solution 10. Chapter 7: Managing Batches and Pipelines 11. Part 4:Secure, Monitor, and Optimize Data Storage and Processing
12. Chapter 8: Implementing Data Security 13. Chapter 9: Monitoring Data Storage and Data Processing 14. Chapter 10: Optimizing and Troubleshooting Data Storage and Data Processing 15. Chapter 11: Accessing the Online Practice Resources 16. Other Books You May Enjoy

Implementing Data Security

In this chapter, you will learn how to recognize sensitive information and implement various sensitive information-handling techniques, such as data masking, row- and column-level security, role-based access and access-controlled lists, encryption, and more. These skills will enable you to design and maintain the security of your data lake and ensure customer privacy.

Note

This chapter primarily focuses on the Implementing data security topic of the DP-203: Data Engineering on Microsoft Azure exam.

By the end of this chapter, you will be able to answer questions on the following confidently:

  • Data masking and data encryption for data at rest and in motion
  • Row-level and column-level security
  • Azure Role-Based Access Control (RBAC)
  • POSIX-like Access Control Lists (ACLs) for ADLS Gen2
  • Data retention policy and secure endpoints (private and public)
  • Resource tokens in Azure Databricks
  • DataFrames and sensitive information
  • ...
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