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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
Author Profile Icon Newton Alex
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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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

Developing a Stream Processing Solution

Building on the foundation of Spark, Azure Data Factory (ADF), and Synapse pipelines, Chapter 5, Developing a Batch Processing Solution, equipped you to effectively process large amounts of data.

In this chapter, you will cover another data method, stream processing solutions, also known as real-time processing systems. Similar to batch processing, stream processing is another important segment of data pipelines. This chapter will focus on introducing the concepts and technologies involved in building a stream processing system. You will be learning about technologies such as Azure Stream Analytics (ASA), Azure Event Hubs, and Spark (from a streaming perspective).

You will learn how to build end-to-end streaming solutions using these technologies and explore important streaming concepts such as checkpointing, windowed aggregates, replaying older stream data, handling drift, and stream management concepts such as distributing streams across...

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