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Data Engineering with AWS

You're reading from   Data Engineering with AWS Learn how to design and build cloud-based data transformation pipelines using AWS

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781800560413
Length 482 pages
Edition 1st Edition
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Author (1):
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Gareth Eagar Gareth Eagar
Author Profile Icon Gareth Eagar
Gareth Eagar
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: AWS Data Engineering Concepts and Trends
2. Chapter 1: An Introduction to Data Engineering FREE CHAPTER 3. Chapter 2: Data Management Architectures for Analytics 4. Chapter 3: The AWS Data Engineer's Toolkit 5. Chapter 4: Data Cataloging, Security, and Governance 6. Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
7. Chapter 5: Architecting Data Engineering Pipelines 8. Chapter 6: Ingesting Batch and Streaming Data 9. Chapter 7: Transforming Data to Optimize for Analytics 10. Chapter 8: Identifying and Enabling Data Consumers 11. Chapter 9: Loading Data into a Data Mart 12. Chapter 10: Orchestrating the Data Pipeline 13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
14. Chapter 11: Ad Hoc Queries with Amazon Athena 15. Chapter 12: Visualizing Data with Amazon QuickSight 16. Chapter 13: Enabling Artificial Intelligence and Machine Learning 17. Chapter 14: Wrapping Up the First Part of Your Learning Journey 18. Other Books You May Enjoy

To get the most out of this book

Basic knowledge of computer systems and concepts, and how these are used within large organizations, is helpful prerequisite knowledge for this book. However, no data engineering-specific skills or knowledge is required. Also, a familiarity with cloud computing fundamentals and core AWS systems will make it easier to follow along, especially with the hands-on exercises, but detailed step-by-step instructions are included for each task.

All hands-on exercises make use of cloud-based services, so beyond using a supported web browser with a stable internet connection, there are no additional hardware or software requirements.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Things change fast in the computing industry, and this is clearly seen within the cloud industry. AWS is constantly rolling out new services, as well as improvements for existing services, and some of these improvements lead to changes in the user interface provided via the AWS console.

As a result, some of the screenshots included in this book may not look identical to what you are seeing in the AWS console when completing hands-on exercises. Or, you may find that a specific screen has additional options beyond what is shown in the screenshot in this book. It is unlikely that these changes will prevent you from following along with the step-by-step instructions in this book, but anything that may significantly impact a hands-on exercise will be addressed with a note for that chapter in this book's GitHub repository. Therefore, please refer to the GitHub repository as you complete the hands-on exercises for each chapter. In addition to notes about any significant console changes, the GitHub repository also includes copies of code contained in this book and other useful resources.

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