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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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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

An Introduction to Data Engineering

Data engineering continues to be a fast-growing career path and a role in high demand, as data becomes ever more critical to organizations of all sizes. For those that enjoy the challenge of putting together the “puzzle pieces” that build out complex data pipelines to ingest raw data, and then transform and optimize that data for varied data consumers, it can be a really rewarding career.

In this chapter, we look at the many ways that data has become an important, and increasingly valuable, corporate asset. We also review some of the challenges that organizations face as they deal with increasing volumes of data, and how data engineers can use cloud-based services to help overcome these challenges. We then set the foundations for the hands-on activities in this book by providing step-by-step details on creating a new Amazon Web Services (AWS) account.

Throughout this book, we are going to cover a number of topics that teach the fundamentals of developing data engineering pipelines on AWS, but we’ll get started in this chapter with these topics:

  • The rise of big data as a corporate asset
  • The challenges of ever-growing datasets
  • The role of the data engineer as a big data enabler
  • The benefits of the cloud when building big data analytic solutions
  • Hands-on – create or access an AWS account for following along with the hands-on activities in this book
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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