Data Engineering with AWS

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.

Type
ebook
Category
publication date
2021-12-29
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

no of pages
482
duration
964
key features
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
approach
Complete with an overview of foundational concepts, discussion of new emerging technologies, and practical, hands-on exercises, this book will demonstrate how to architect and build complex data pipelines using AWS services. A companion GitHub repository provides copies of all included code.
audience
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.
meta description
The missing expert-led manual for the AWS ecosystem — go from foundations to building data engineering pipelines effortlessly

Purchase of the print or Kindle book includes a free eBook in the PDF format.
short description
This book will help you on your journey toward architecting and building data engineering pipelines on AWS. You'll learn about (and get hands-on with) AWS services for ingesting, transforming, and consuming data. Whether you're new to data engineering or just new to data engineering on AWS, this book will be an invaluable guide.
subtitle
Learn how to design and build cloud-based data transformation pipelines using AWS
keywords
AWS cloud, data engineering books, AWS data engineering, data architecture, data science
Product ISBN
9781800560413