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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

Chapter 1: An Introduction to Data Engineering

Data engineering is 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 to then transform and optimize that data for various 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 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 rest of 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
Published in: Dec 2021
Publisher: Packt
ISBN-13: 9781800560413
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