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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
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Giacinto Palmieri
Mr. Surendra Mettapalli Mr. Surendra Mettapalli
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Mr. Surendra Mettapalli
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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

Storage

In today’s data-driven world, storing and managing vast amounts of information is crucial. Consider ADLS Gen2 as your data lake storage. Azure Data Lake Storage Gen2 (ADLS Gen2) offers a secure and scalable solution specifically designed for Big Data Analytics.

You can create the following folder structure to handle your batch pipeline:

  • The raw trip data can be stored here: iac/raw/trips/2024/01/01.
  • The cleaned-up data can be copied over to the transform/in folder: iac/transform/in/2024/01/01.
  • The output of the transformed data can be moved into the transform/out folder: iac/transform/out/2024/01/01.
  • Finally, you can import the data from transform/out into a Synapse SQL dedicated pool using PolyBase.

Note that tools such as ADF and PolyBase also provide the ability to directly move data between Spark and Synapse SQL dedicated pools. You can choose this direct approach instead of storing the intermediate data in the data lake if that works...

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