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AWS Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice
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There's no better time to become a data engineer. And acing the AWS Certified Data Engineer Associate (DEA-C01) exam will help you tackle the demands of modern data engineering and secure your place in the technology-driven future.
Authors Sakti Mishra, Dylan Qu, and Anusha Challa equip you with the knowledge and sought-after skills necessary to effectively manage data and excel in your career. Whether you're a data engineer, data analyst, or machine learning engineer, you'll discover in-depth guidance, practical exercises, sample questions, and expert advice you need to leverage AWS services effectively and achieve certification. By reading, you'll learn how to:
- Ingest, transform, and orchestrate data pipelines effectively
- Select the ideal data store, design efficient data models, and manage data lifecycles
- Analyze data rigorously and maintain high data quality standards
- Implement robust authentication, authorization, and data governance protocols
- Prepare thoroughly for the DEA-C01 exam with targeted strategies and practices
- ISBN-101098170075
- ISBN-13978-1098170073
- Edition1st
- PublisherO'Reilly Media
- Publication dateSeptember 30, 2025
- LanguageEnglish
- Dimensions7 x 0.96 x 9.19 inches
- Print length473 pages
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From the Publisher
What This Book Is About
This book is designed to be your comprehensive guide to mastering the skills for the AWS Certified Data Engineer Associate (DEA-C01) certification. Our goal is to provide a clear path from foundational concepts to advanced, practical application.
By the end of this book, you will understand:
- The format of the DEA-C01 exam, how to prepare effectively, and strategies for success on test day
- The key responsibilities and mindset of an AWS Certified Data Engineer
- How core AWS database, analytics, and auxiliary services function and how to apply them to solve real-world data challenges
- The art of selecting the right services to architect solutions that are optimized for cost, performance, security, and high availability
What This Book Isn’t
Before we detail what this book covers, it’s important to clarify what it isn’t. This book is not an exhaustive deep dive into a single AWS service, nor is it a comprehensive manual for hands-on implementation. While many excellent books approach data engineering from a specific technology perspective, their focus can be narrow. Instead, our goal is to provide comprehensive coverage of the fundamental concepts and architectural patterns for data engineering on AWS.
Who Should Read This Book
Our primary audience is any technical practitioner who wants to prepare for the DEA-C01 certification. This guide is crafted to serve a diverse group of professionals, and you will find this book especially valuable if you are:
- A software engineer, data scientist, or data analyst interested in transitioning into data engineering. We provide the foundational knowledge and practical AWS skills needed to make a successful career pivot.
- A current data engineer focused on specific technologies who wants to broaden their perspective across the entire AWS data ecosystem. This book will help you connect the dots and build a more comprehensive skill set.
Editorial Reviews
About the Author
He is passionate about technologies and is always curious to learn about the latest innovations happening in the technology domain. During his career he has gained expertise in multiple industry domains and technologies such as Big Data, Analytics, Machine Learning, Artificial Intelligence, Relational/NoSQL/Graph Databases, Web/Mobile Application development and cloud technologies such as Amazon Web Services & Google Cloud Platform.
Dylan Qu is a technology leader, architect, engineer, and public speaker with 8 years of experience in the IT industry. He currently works at Amazon Web Services (AWS) as a Principal Solutions Architect, where he helps customers architect highly scalable, performant, and secure data solutions on AWS. Dylan has authored various blogs and whitepapers across a diverse range of technologies, such as big data, serverless, IoT and machine learning. He is passionate about new technologies and adept at turning technical innovations into production workloads at scale.
Anusha Challa brings over 14 years of comprehensive experience to the analytics and data warehousing field. She worked with 100s of diverse clients and developed scalable data architectures to meet specific organizational needs. With a master’s degree in computer science specializing in Machine Learning from Georgia Tech University, Anusha has authored informative blogs and whitepapers covering topics such as data warehousing, data security, Machine Learning, and Artificial Intelligence. Anusha's expertise extends to public speaking engagements, where she has delivered presentations at major events including AWS re:Invent and the AWS Summit in New York, sharing her insights on data analytics and cloud computing. Passionate about her work, Anusha remains dedicated to exploring emerging technologies and industry trends in data analytics.
Product details
- Publisher : O'Reilly Media
- Publication date : September 30, 2025
- Edition : 1st
- Language : English
- Print length : 473 pages
- ISBN-10 : 1098170075
- ISBN-13 : 978-1098170073
- Item Weight : 1.82 pounds
- Dimensions : 7 x 0.96 x 9.19 inches
- Best Sellers Rank: #1,137,016 in Books (See Top 100 in Books)
- #353 in Data Modeling & Design (Books)
- #583 in Cloud Computing (Books)
- #834 in Computer & Technology Certification Guides
- Customer Reviews:














