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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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Newton Alex Newton Alex
Author Profile Icon Newton Alex
Newton Alex
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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

Designing for data privacy and managing sensitive information

Any organization that handles sensitive information is usually bound by its country or state laws and other compliance regulations to keep the data secure and confidential. Aside from legal reasons, keeping sensitive data protected is very important for the reputation of an organization and to reduce the risk of identity theft for its customers. Azure security standards recommend the following techniques to keep sensitive data safe:

  • Identifying and classifying sensitive data – The very first step is to analyze and identify all the sensitive data in your data stores. Some might be straightforward, such as SQL tables or structured files, and some might be not so straightforward, such as PII data being logged in log files. Azure also provides tools that can help with the identification and classification of data. For example, the Synapse SQL portal provides a feature for Data Discovery and Classification, which...
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