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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

Developing a Batch Processing Solution

In Chapter 4, Ingesting and Transforming Data, you learned about services such as Spark, Azure Data Factory (ADF), and Synapse SQL. You will continue doing so here and learn about a few more batch-processing-related technologies.

In this chapter, you will develop robust batch-processing solutions using Azure’s analytics services such as Data Lake Storage, Databricks, Synapse Analytics, and Data Factory. Focus areas include optimizing SQL pool data loading with PolyBase and implementing Azure Synapse Link for seamless data querying. You’ll create scalable data pipelines, optimize batch sizes, and ensure pipeline integrity through rigorous testing. Integration of notebooks will enhance analytical capabilities.

You will also master data manipulation techniques such as upserting, reverting data states, configuring advanced exception handling, and managing batch retention policies for effective data life cycle management. Interacting...

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