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

Product type Paperback

Published in Oct 2023

Publisher Packt

ISBN-13 9781804614426

Length 636 pages

Edition 2nd Edition

Tools

AWS

Concepts

Data Engineering

Author (1):

Gareth Eagar

View More author details

Table of Contents (24) Chapters

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...