Data Fabric Technologies and Systems includes emerging data management ecosystems and frameworks, covering the principles, architectures, and technologies that underpin data fabric solutions. The book presents multiple industry platforms and data ecosystems within a unified framework, enabling readers to comprehend, compare and evaluate different approaches to managing, processing and performing analytics on data at scale.  It covers data integration, compliance, governance, metadata management, and the transformative role of AI/ML, including Large Language Models (LLMs), in optimizing data pipelines and analytics. With real-world case studies, practical examples, and emerging trends, this book prepares professionals working on big data, graduate-level students, information systems students and researchers with the tools and insights needed to build scalable, efficient, and adaptive real-time data system solutions for today’s complex, data-driven world.

Chapters are self-contained and conclude with end-of-chapter questions, exercises, projects, open research problems and insights into future developments, such as LLMs in data fabrics, agentic data systems, cloud-native data fabric and advancements, decentralized data architectures and next-generation data stacks.

Kamalakar Karlapalem is a Professor at the International Institute of Information Technology Hyderabad (IIIT-Hyderabad), India. His research focuses on database systems, data visualization, data mining, text analytics, workflow systems, and autonomous multi-agent systems.

Radha Krishna Pisipati is a Professor in the Department of Computer Science and Engineering at the National Institute of Technology (NIT) Warangal, India. His research and innovation span data mining, data fabric, multimodal data-driven systems, deep learning, and generative and agentic AI.