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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

Performing Data Exploratory Analysis

Data exploration is much easier from inside Synapse Studio, as it provides easy one-click options to examine various formats of data. You can learn about some of the options available for data exploration using Spark, SQL, and ADF/Synapse pipelines.

Note

This section primarily focuses on the Perform data exploratory analysis concept of the DP-203: Data Engineering on Microsoft Azure exam.

Data Exploration Using Spark

Data exploration is a crucial step in the data analysis process, allowing you to analyze the patterns and correlations within data. Apache Spark, an open source distributed processing system in Azure for data exploration, offers a powerful and scalable approach for handling large datasets efficiently.

Perform the following steps to do so:

  1. From within the Synapse Studio, right-click on the data file and select the Load to DataFrame option, as shown in Figure 4.56:
Figure 4.56 – The image depicts a user interface for managing data files within a Synapse workspace. It shows a file directory and a context menu with the option “Load to DataFrame” highlighted, indicating the action to load data from a selected file into a DataFrame for analysis or manipulation.

Figure 4.56 –...

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