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Data Engineering with AWS

Data Engineering with AWS - Second Edition

By : Gareth Eagar
4.8 (31)
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Data Engineering with AWS

Data Engineering with AWS

4.8 (31)
By: Gareth Eagar

Overview of this book

This book, authored by a Senior Data Architect with 25 years of experience, helps you gain expertise in the AWS ecosystem for data engineering. This revised edition updates every chapter to cover the latest AWS services and features, provides a refreshed view on data governance, and introduces a new section on building modern data platforms. You will learn how to implement a data mesh, work with open-table formats such as Apache Iceberg, and apply DataOps practices for automation and observability. You will begin by exploring core concepts and essential AWS tools used by data engineers, along with modern data management approaches. You will then design and build data pipelines, review raw data sources, transform data, and understand how it is consumed by various stakeholders. The book also covers data governance, populating data marts and warehouses, and how a data lakehouse fits into the architecture. You will explore AWS tools for analysis, SQL queries, visualizations, and learn how AI and machine learning generate insights from data. Later chapters cover transactional data lakes, data meshes, and building a complete AWS data platform. By the end, you will be able to confidently implement data engineering pipelines on AWS. *Email sign-up and proof of purchase required
Table of Contents (24 chapters)
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1
Section 1: AWS Data Engineering Concepts and Trends
6
Section 2: Architecting and Implementing Data Engineering Pipelines and Transformations
13
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
17
Section 4: Modern Strategies: Open Table Formats, Data Mesh, DataOps, and Preparing for the Real World
22
Other Books You May Enjoy
23
Index

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

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ISBN: 9781839214189

  • Understand how data engineering supports data science workflows
  • Discover how to extract data from files and databases and then clean, transform, and enrich it
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Data Engineering with AWS
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