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Data Management for Agentic Systems
book

Data Management for Agentic Systems

by Michael Bachman
September 2026
Intermediate to advanced
100 pages
1h 7m
English
O'Reilly Media, Inc.

Overview

Data Management for AI and Agentic Systems offers a foundational guide to designing robust data pipelines for AI models and agents. As demand for AI-driven decision-making grows, many systems fail because of poor or unreliable data. This book focuses on a critical—but often overlooked—component of success: structured, trustworthy, and context-rich data.

Author Michael Bachman draws on decades of experience to bridge the gap between data engineering and AI development. With practical strategies, case studies, and real-world code examples, readers will learn to align AI and data systems for greater accuracy, scalability, and performance in production environments.

  • Solve challenges in data quality, governance, and ingestion
  • Prevent failures like hallucinations and model drift with better data
  • Design agent-ready datasets rooted in domain-specific structure
  • Automate data validation and monitoring to maintain trust
  • Align data workflows with modern AI and agentic architectures
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Publisher Resources

ISBN: 9798341649545Errata Page