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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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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 to purge data based on business requirements

Data purging is another overlapping concept with data retention. Data purging refers to the process of safely deleting data as per business requirements. Let's look at the options available in Azure Data Lake Storage and Azure Synapse SQL.

Purging data in Azure Data Lake Storage Gen2

There are two ways in which we can achieve scheduled data deletion or data purging. One is the same as data retention, using life cycle management in Azure Storage. The second technique is to use Azure Data Factory. Whenever we delete data in Azure, it ensures that the storage locations are overwritten so that the deleted data cannot be retrieved by a malicious user. You can refer to Microsoft's data protection policy here: https://docs.microsoft.com/en-us/azure/security/fundamentals/protection-customer-data.

We can periodically or conditionally delete files from Azure Storage using the Delete Activity in ADF. We have already seen...

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