BÜCHER VERSANDKOSTENFREI INNERHALB DEUTSCHLANDS
Data Engineering with Generative and Agentic AI on AWS
Building an AI-Augmented Data Practice for the Enterprise
Apress
ISBN 9798868821981
Standardpreis
Bibliografische Daten
Fachbuch
Buch. Softcover
2026
Format (B x L): 17,8 x 25,4 cm
Verlag: Apress
ISBN: 9798868821981
Produktbeschreibung
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.
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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