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Data Engineering with AWS

You're reading from   Data Engineering with AWS Acquire the skills to design and build AWS-based data transformation pipelines like a pro

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781804614426
Length 636 pages
Edition 2nd 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 (24) Chapters Close

Preface 1. Section 1: AWS Data Engineering Concepts and Trends
2. An Introduction to Data Engineering FREE CHAPTER 3. Data Management Architectures for Analytics 4. The AWS Data Engineer’s Toolkit 5. Data Governance, Security, and Cataloging 6. Section 2: Architecting and Implementing Data Engineering Pipelines and Transformations
7. Architecting Data Engineering Pipelines 8. Ingesting Batch and Streaming Data 9. Transforming Data to Optimize for Analytics 10. Identifying and Enabling Data Consumers 11. A Deeper Dive into Data Marts and Amazon Redshift 12. Orchestrating the Data Pipeline 13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
14. Ad Hoc Queries with Amazon Athena 15. Visualizing Data with Amazon QuickSight 16. Enabling Artificial Intelligence and Machine Learning 17. Section 4: Modern Strategies: Open Table Formats, Data Mesh, DataOps, and Preparing for the Real World
18. Building Transactional Data Lakes 19. Implementing a Data Mesh Strategy 20. Building a Modern Data Platform on AWS 21. Wrapping Up the First Part of Your Learning Journey 22. Other Books You May Enjoy
23. Index

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/Draw.IO template for this via the GitHub site of this book at https://github.com/PacktPublishing/Data-Engineering-with-AWS-2nd-edition/blob/main/Chapter05/Data-Engineering-Whiteboard-Template.drawio.

Figure 5.7: Generic whiteboarding template

Note that the three zones included in the template (landing zone, clean zone, and curated...

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