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Data Engineering with AWS
Data Engineering with AWS

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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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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2023
Length: 636 pages
Edition : 2nd
Language : English
ISBN-13 : 9781804614426
Category :
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Product Details

Publication date : Oct 31, 2023
Length: 636 pages
Edition : 2nd
Language : English
ISBN-13 : 9781804614426
Category :
Tools :

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(30 Ratings)
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adit modi Feb 01, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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!
Amazon Verified review Amazon
Paul Gerber Nov 10, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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!
Amazon Verified review Amazon
Vishwanath Gorti Jan 06, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Author Gareth Eagar, very well illustrated the content from the beginning of Data Engineering inception phase to advanced topics to be expertise level with his gained experience. Data Engineers can apply their learning of from data analysis skills to extract insights from large data sets and visualize.Author very well elevated book with latest happenings in Artificial Intelligence & Machine Learning including Gen AI, which is much useful for Data Scientist to enhance their skill. Overall it is a highly recommended for Data Scientists aspirers.
Amazon Verified review Amazon
Dwayne Natwick Feb 15, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I received a copy of Packt Publishing’s Data Engineering with AWS by Gareth Eagar. This is a very detailed and definitive guide to data engineering as it relates to AWS. The information provided is also helpful for guidance about data engineering overall as well. This book covers the full process of data engineering from roles, architecture, analytics, AWS tools, security, governance, and transforming through data pipelines. The ability for the author to communicate the concepts and relate them to overall data engineering pipelines as well as the detail of architecting these pipelines into AWS is exceptional. Gareth does not simply focus on architecture and pipelines to analyze and transform data, he also provides a complete chapter that covers the role of AI and machine learning into the data engineering process with AWS tools like Amazon SageMaker and Amazon Bedrock. This is an extremely comprehensive book that provides guidance to anyone that is performing any level of data engineering and data architecture in AWS. This book is highly recommended if you are working with data in AWS or any other cloud provider.
Amazon Verified review Amazon
Souvik Roy Nov 01, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book is great to start with for people who are transitioning into data engineering. I am using it into my academics to understand the essence of data engineering and trying to implement in real world projects. I would recommend people who want to study data engineering from scratch.
Amazon Verified review Amazon
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