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Key benefits

Learn about common data architectures and modern approaches to generating value from big data

Explore AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines

Learn how to architect and implement data lakes and data lakehouses for big data analytics from a data lakes expert

Description

Written by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS. As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data. By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.

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

Understand data engineering concepts and emerging technologies

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

Run complex SQL queries on data lake data using Amazon Athena

Load data into a Redshift data warehouse and run queries

Create a visualization of your data using Amazon QuickSight

Extract sentiment data from a dataset using Amazon Comprehend

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Download this book in EPUB and PDF formats

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Frequently bought together

Data Engineering with Apache Spark, Delta Lake, and Lakehouse

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Total $ 165.97

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Amazon verified reviews

J. Dadd Jan 10, 2022

Buy this book if you want to learn some theory and then be shown how to implement the concepts introduced on AWS. This is not a high-brow textbook heavy on theory. It is great for anyone considering using AWS for data warehousing and data engineering, especially generalist infrastructure architects (like myself) who do not focus purely on this space.Gareth deftly sets the scene by providing a useful review of data warehousing technology over time, and how the modern data management landscape has been shaped. Each section of the book starts with a solid theoretical introduction followed by a clear, useful, and most importantly technically detailed how-to guide for implementing each new concept within the AWS environment.I especially like the section on AI / ML; Gareth and his co-contributors succinctly describe how to knit together multiple AWS services to produce a working end-to-end data analytics solution. There are also invaluable bonus sections, such as how to manage a data engineering project, from identifying stakeholders, running whiteboarding sessions, identifying data sources, pipelines, and toolsets.As stated in the introduction, this book alone will not magically turn you into a data engineer. What it will do, however, is give you a solid theoretical and technical foundation in all key concepts, as well as offer insights into future trends. This book is an invaluable point of reference as you progress on your data engineering journey within the AWS ecosystem.

Amazon Verified review

Christoph Jan 26, 2022

Ein gelungenes Buch zum Thema ETL und Big Data in AWS. Für meinen Geschmack genau die richtige Mischung zwischen Breite und Tiefe mit praxisnahen Anwendungsfällen - das sage ich als erfahrener Cloud Engineer.

SANTI TEERAGUL Aug 20, 2022

That’s great for my new job using AWS

Very informative book, contains all conepts Oct 22, 2024

Very informative book covering all the concepts in easy manner

JB Feb 06, 2022

I recently read the book Data Engineering with AWS. A pre-release copy was provided to me by the publisher and I was asked to give my honest/unbiased opinion below.This book is geared towards early career Data Engineers or experienced Software/Data Engineers who are not familiar with AWS services for data management. For its intended audience, the book does a great job explaining the fundamentals of Data Engineering from end-to-end. It takes the reader through a journey from the “what, why, who and how.” It also thoroughly described the wide variety of AWS services used for managing data (e.g., Redshift, S3, Kinesis, SageMaker, etc.) along the way.There aren't really any issues with the book. The only piece I was concerned about is the hands-on exercises. Although I think they are useful, they will inevitably become dated as the software and user interfaces change. So, a perspective reader should be careful to look at the publish date of the book and remain flexible if some of the instructions don’t match the latest version of the systems. To counter act that, the preface of the book contain a GitHub repo link with the promise of keeping it up to date. Ultimately, I believe a large percentage of the book will age gracefully over time.Overall, I think the book is a good, well-written, comprehensive overview of Data Engineering using AWS services and I enjoyed going through it and plan on keeping it as a quick reference guide.

Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS

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