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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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Data Engineering with AWS

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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 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

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 : 9781804613139
Category :

What do you get with eBook?

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Product Details

Publication date : Oct 31, 2023
Length: 636 pages
Edition : 2nd
Language : English
ISBN-13 : 9781804613139
Category :

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Table of Contents

23 Chapters
Section 1: AWS Data Engineering Concepts and Trends Chevron down icon Chevron up icon
An Introduction to Data Engineering Chevron down icon Chevron up icon
Data Management Architectures for Analytics Chevron down icon Chevron up icon
The AWS Data Engineer’s Toolkit Chevron down icon Chevron up icon
Data Governance, Security, and Cataloging Chevron down icon Chevron up icon
Section 2: Architecting and Implementing Data Engineering Pipelines and Transformations Chevron down icon Chevron up icon
Architecting Data Engineering Pipelines Chevron down icon Chevron up icon
Ingesting Batch and Streaming Data Chevron down icon Chevron up icon
Transforming Data to Optimize for Analytics Chevron down icon Chevron up icon
Identifying and Enabling Data Consumers Chevron down icon Chevron up icon
A Deeper Dive into Data Marts and Amazon Redshift Chevron down icon Chevron up icon
Orchestrating the Data Pipeline Chevron down icon Chevron up icon
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning Chevron down icon Chevron up icon
Ad Hoc Queries with Amazon Athena Chevron down icon Chevron up icon
Visualizing Data with Amazon QuickSight Chevron down icon Chevron up icon
Enabling Artificial Intelligence and Machine Learning Chevron down icon Chevron up icon
Section 4: Modern Strategies: Open Table Formats, Data Mesh, DataOps, and Preparing for the Real World Chevron down icon Chevron up icon
Building Transactional Data Lakes Chevron down icon Chevron up icon
Implementing a Data Mesh Strategy Chevron down icon Chevron up icon
Building a Modern Data Platform on AWS Chevron down icon Chevron up icon
Wrapping Up the First Part of Your Learning Journey Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(31 Ratings)
5 star 83.9%
4 star 16.1%
3 star 0%
2 star 0%
1 star 0%
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Liuquan Feb 04, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Best coverage on modern data warehousing technologies and best practices! L Tong
Subscriber review Packt
Pauline Nov 04, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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 Amazon
Arden Feb 01, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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!
Amazon Verified review Amazon
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
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