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Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide - Second Edition

By : Giacinto Palmieri, Surendra Mettapalli, Newton Alex
4.6 (16)
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Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

4.6 (16)
By: Giacinto Palmieri, Surendra Mettapalli, Newton Alex

Overview of this book

One of the top global cloud providers, Azure offers extensive data hosting and processing services, driving widespread cloud adoption and creating a high demand for skilled data engineers. The Azure Data Engineer Associate (DP-203) certification is a vital credential, demonstrating your proficiency as an Azure data engineer to prospective employers. This comprehensive exam guide is designed for both beginners and seasoned professionals, aligned with the latest DP-203 certification exam, to help you pass the exam on your first try. The book provides a foundational understanding of IaaS, PaaS, and SaaS, starting with core concepts like virtual machines (VMs), VNETS, and App Services and progressing to advanced topics such as data storage, processing, and security. What sets this exam guide apart is its hands-on approach, seamlessly integrating theory with practice through real-world examples, practical exercises, and insights into Azure's evolving ecosystem. Additionally, you'll unlock lifetime access to supplementary practice material on an online platform, including mock exams, interactive flashcards, and exam tips, ensuring a comprehensive exam prep experience. By the end of this book, you’ll not only be ready to excel in the DP-203 exam, but also be equipped to tackle complex challenges as an Azure data engineer.
Table of Contents (17 chapters)
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1
Part 1: Azure Basics
3
Part 2: Data Storage
6
Part 3:Data Processing
11
Part 4:Secure, Monitor, and Optimize Data Storage and Processing

Summary

With that, you have come to the end of the second chapter. In this chapter, you learned about the different partitioning techniques available in Azure. You started with the basics of partitioning and its benefits of partitioning, before moving on to partitioning techniques for storage and analytical workloads. You next explored the best practices to improve partitioning efficiency and performance and reviewed the concept of distribution tables and how they impact the partitioning of Azure Synapse Analytics. Finally, you studied storage limitations, which play an important role in deciding when to partition for ADLS Gen2.

This covers the syllabus for the Implement a Partition Strategy topic for the DP-203 exam. You will reinforce the learnings from this chapter via implementation details and tips in Chapter 6, Developing a Stream Processing Solution.

The next chapter, Chapter 3, Designing and Implementing the Data Exploration Layer, will explore the concepts of Azure Synapse...

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