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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
Tools
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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

Summary

In this chapter, we reviewed how data is becoming ever more important for organizations looking to gain new insights and competitive advantage, and introduced some core big data processing technologies and approaches. We also looked at the key roles related to managing, processing, and analyzing large datasets, and highlighted how cloud technologies enable organizations to better deal with the increasing volume and variety of data.

In our first hands-on exercise, we provided step-by-step instructions for creating a new AWS account, which can be used through the remainder of this book as we develop our own data engineering pipeline.

In the next chapter, we dig deeper into current approaches, tools, and frameworks that are commonly used to manage and analyze large datasets, including data warehouses, data marts, data lakes, and data mesh. We also get hands-on with AWS again, but this time we will use the AWS Command Line Interface (CLI) to create new Amazon S3 buckets.

Learn more on Discord

To join the Discord community for this book – where you can share feedback, ask questions to the author, and learn about new releases – follow the QR code below:

https://discord.gg/9s5mHNyECd

You have been reading a chapter from
Data Engineering with AWS - Second Edition
Published in: Oct 2023
Publisher: Packt
ISBN-13: 9781804614426
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