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Home > Computing and Information Technology > Computer science > Artificial intelligence > Data Engineering with Generative and Agentic AI on AWS: Building an AI-Augmented Data Practice for the Enterprise
Data Engineering with Generative and Agentic AI on AWS: Building an AI-Augmented Data Practice for the Enterprise

Data Engineering with Generative and Agentic AI on AWS: Building an AI-Augmented Data Practice for the Enterprise

          
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About the Book

Unlock the future of cloud data engineering with generative and agentic AI on AWS.

This hands-on guide shows you how to build intelligent, responsive data platforms using cutting-edge AI capabilities and modern AWS services.

Learn to design next-generation data architectures--from data lakes and data mesh to scalable pipelines and real-time analytics. Discover how generative AI and agentic automation are transforming every aspect of enterprise data work: ingesting unstructured data, enabling semantic search with Retrieval-Augmented Generation (RAG), building autonomous data agents, and using natural language interfaces to turn business questions into instant insights.

Author Justin J. Leto, PE, MBA, PMP, is a Principal Solutions Architect at AWS with over 20 years of experience in data engineering and AI. He doesn't just teach today's techniques--he prepares you for the future disruptions reshaping the field. His book is essential reading for current and aspiring data engineers, data analysts, data architects, engineering managers, CTOs, CDOs, and data-focused entrepreneurs looking to gain an edge over the competition.

What You Will Learn:

  • Master the core principles and practices of data engineering to build a long, successful career in the field.
  • Accelerate your impact using AWS cloud services for scalable, modern data solutions.
  • Explore how the role of the modern data engineer is evolving to support generative and agentic AI use cases.
  • Develop a modern data strategy by working backwards from business goals to gain buy-in from CxO-level leadership.
  • Design and deploy modern data architectures--including data lakes, data mesh, and data marts--and understand when to use each.
  • Apply generative and agentic AI to enhance every stage of the data engineering lifecycle.
  • Evaluate emerging data and AI technologies using proven methodology to separate real value from hype.
  • Prepare for the future of data engineering powered by autonomous agents that scale enterprise impact.

Who this Book Is For:

Data engineers, analysts, architects, and tech leaders seeking practical guidance on AWS data engineering and generative AI, with or without prior cloud experience.


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Product Details
  • ISBN-13: 9798868821981
  • Publisher: Apress
  • Publisher Imprint: Apress
  • Height: 254 mm
  • Returnable: N
  • Width: 178 mm
  • ISBN-10: 8868821982
  • Publisher Date: 11 Aug 2025
  • Binding: Paperback
  • Language: English
  • Sub Title: Building an AI-Augmented Data Practice for the Enterprise


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