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Key benefits

Delve into robust AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines

Stay up to date with a comprehensive revised chapter on Data Governance

Build modern data platforms with a new section covering transactional data lakes and data mesh

Description

This book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability. You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS. By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!

Who is this book for?

This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts, while gaining practical experience with common data engineering services on AWS, will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book, but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.

What you will learn

Seamlessly ingest streaming data with Amazon Kinesis Data Firehose

Optimize, denormalize, and join datasets with AWS Glue Studio

Use Amazon S3 events to trigger a Lambda process to transform a file

Load data into a Redshift data warehouse and run queries with ease

Visualize and explore data using Amazon QuickSight

Extract sentiment data from a dataset using Amazon Comprehend

Build transactional data lakes using Apache Iceberg with Amazon Athena

Learn how a data mesh approach can be implemented on AWS

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Packt verified reviews

Amazon verified reviews

Liuquan Feb 04, 2024

Best coverage on modern data warehousing technologies and best practices! L Tong

Subscriber review

Pauline Nov 04, 2023

Beginning to get into data engineering and this book has been helpful.- It is comprehensive and covers a wide range of data engineering topics.- It is hands-on and provides practical examples and step-by-step instructions.

Amazon Verified review

Arden Feb 01, 2024

I have been awestruck by the way Gareth gets his work done, the simplest of ways to get complex stuff published, he is a genius and I will rely on him to lover complexity to a completely new level!

adit modi Feb 01, 2024

Gareth Eagar's "Data Engineering with AWS" is a gem for anyone stepping into or already navigating the realm of data engineering. With a clear and approachable style, Eagar takes you on a journey through various AWS services essential for data engineering, offering a perfect blend of theory and real-world application.Whether you're new to the field or a seasoned professional, this book provides a comprehensive understanding of data engineering processes. Eagar covers everything from collecting and transforming raw data to utilizing AWS services like Glue, Athena, and Kinesis. The real beauty lies in how he simplifies complex concepts, making it a delightful read for beginners and an insightful refresher for professionals. Highly recommended!

Paul Gerber Nov 10, 2023

Gareth Eaga's "Data Engineering with AWS, Second Edition" stands out as an exceptional resource for those eager to master AWS data engineering, offering a comprehensive exploration that extends even to the intricate realm of deployment pipelines. As a seasoned Power BI developer and data analyst, I found this edition to be an indispensable tool in advancing my skills, particularly in the context of efficient and scalable deployment strategies.Eaga takes a hands-on approach, demystifying AWS data engineering concepts while seamlessly integrating insights into deployment pipeline best practices. This edition doesn't just stop at the fundamentals; it delves into the intricacies of continuous integration, continuous deployment, and the orchestration of data workflows. Practical examples and step-by-step tutorials abound, ensuring that readers not only comprehend the theory but also gain the skills to implement effective deployment strategies in real-world scenarios.What sets this edition apart is its relevance to the latest AWS advancements, making it a must-have for both beginners and seasoned practitioners. Eaga's clear and engaging writing style, coupled with real-world examples, facilitates a smooth learning curve. Whether you're establishing data lakes, implementing ETL processes, or maneuvering through the complexities of deployment pipelines, this book provides the insights and tools necessary to navigate the AWS data engineering landscape with confidence.The inclusion of deployment pipeline considerations adds significant value to the book, making it an all-encompassing guide for professionals aiming to excel in cloud-based data engineering. Gareth Eaga's expertise shines through, offering practical wisdom that extends seamlessly into the critical domain of deployment pipelines. Highly recommended for anyone serious about mastering AWS data services and deployment strategies alike!

Data Engineering with AWS: Acquire the skills to design and build AWS-based data transformation pipelines like a pro , Second Edition

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