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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

Transformation

Once your data is in a clean format and prepared for further activities such as transformations, you can run the transformation logic using services such as Spark, SQL, and Hive. In this example, as per the certification syllabus, you will use ADB Spark. But first, you need to create an ADB workspace, followed by the ADB cluster that will run the transformations, and then write the Spark code within the Cmd blocks. Perform the following steps to do so:

  1. Select Azure Databricks from the Azure portal and click +Create to create a new workspace. Figure 5.8 shows the Create an Azure Databricks workspace screen.
  2. Enter the name for the workspace beside the Workspace name option. In this case, it is DP-203-databricks-workspace. Then select an option from the Region dropdown. In this case, it is UK South.
  3. Next, select an option from the Pricing Tier dropdown. In this case, it is Standard (Apache Spark, Secure with Microsoft Entra ID) (Figure 5.8):
    Figure 5.8 – The image illustrates the Azure Databricks workspace creation screen on Microsoft Azure, displaying fields for entering “project details” such as “subscription,” “resource group,” and “instance details” including “workspace name,” “region,” and “pricing tier,” with options to review, create, or navigate to networking settings.

Figure...

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