AWS Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice

by Sakti Mishra, Dylan Qu, Anusha Challa

Overview

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

Product Details

ISBN-13:	9781098170035
Publisher:	O'Reilly Media, Incorporated
Publication date:	08/25/2025
Sold by:	Barnes & Noble
Format:	eBook
Pages:	476
File size:	17 MB
Note:	This product may take a few minutes to download.

About the Author

Sakti Mishra is an engineer, architect, author and technology leader with more than 18 years of working experience in the IT product and service industry. He is currently working as a Principal Solutions Architect at Amazon Web Services, where he helps customers solve complex data and analytics related problems with cloud native architecture patterns.

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.