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Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide - Second Edition

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

Azure Data Engineer Associate Certification Guide

4.6 (16)
By: Palmieri, Surendra Mettapalli, 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

Implementing a Streaming Use Case with Azure

Stream processing systems, or real-time processing systems, are systems that perform data processing in near real time. Think of stock market updates, real-time traffic updates, and real-time credit card fraud detection. Incoming data is processed as and when it arrives with very minimal latency, usually in the range of milliseconds to seconds. This section primarily focuses on the Create a stream processing solution by using Stream Analytics and Azure Event Hubs concept of the DP-203: Data Engineering on Microsoft Azure exam.

The streaming pipeline, as depicted by the gray boxes in Figure 6.1, involves several key stages:

  • Real-time ingestion: This is where data is captured and imported into the system.
  • Stream processing: This involves the real-time analysis and manipulation of the ingested data.
  • Analytical data store: This is where processed data is stored for further analysis.
  • Analytics and reporting: This is the...
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