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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

Hands-on – architecting a sample pipeline

For the hands-on portion of this chapter, you will review the detailed notes from a whiteboarding session held for the fictional company GP Widgets Inc. As you go through the notes, you should create a whiteboard architecture, either on an actual whiteboard or on a piece of poster board. Alternatively, you can create the whiteboard using a free online design tool, such as the one available at http://diagrams.net.

As a starting point for your whiteboarding session, you can use the following template. You can recreate this on your whiteboard or poster board, or you can access the diagrams.net template for this via the GitHub site for of this book:

Figure 5.7 – Generic whiteboarding template

Note that the three zones included in the template (landing zone, clean zone, and curated zone) are commonly used for data lakes. However, some data lakes may only have two zones, while others may have four or more...

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