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Azure Data Engineer Associate Certification Guide

You're reading from Azure Data Engineer Associate Certification Guide

Product type Book

Published in Feb 2022

Publisher Packt

ISBN-13 9781801816069

Pages 574 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Newton Alex

Table of Contents (23) Chapters

Preface

Part 1: Azure Basics

Chapter 1: Introducing Azure Basics

Part 2: Data Storage

Chapter 2: Designing a Data Storage Structure

Chapter 3: Designing a Partition Strategy

Chapter 4: Designing the Serving Layer

Chapter 5: Implementing Physical Data Storage Structures

Chapter 6: Implementing Logical Data Structures

Chapter 7: Implementing the Serving Layer

Part 3: Design and Develop Data Processing (25-30%)

Chapter 8: Ingesting and Transforming Data

Chapter 9: Designing and Developing a Batch Processing Solution

Chapter 10: Designing and Developing a Stream Processing Solution

Chapter 11: Managing Batches and Pipelines

Part 4: Design and Implement Data Security (10-15%)

Chapter 12: Designing Security for Data Policies and Standards

Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)

Chapter 13: Monitoring Data Storage and Data Processing

Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing

Part 6: Practice Exercises

Chapter 15: Sample Questions with Solutions

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Part 6: Practice Exercises

This part focuses on where we put everything we have learned into practice. We will explore a bunch of real-world problems and learn how to use the information we learned in the previous chapters. This will help you prepare for both the exam and real-world problems.

This section comprises the following chapter:

Chapter 15, Sample Questions with Solutions

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Azure Data Engineer Associate Certification Guide

Published in: Feb 2022 Publisher: Packt ISBN-13: 9781801816069

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Authors (1)

Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.

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