Data Fabric Technologies and Systems

Unifying Data Ecosystems, Data Science, AI and Data Agents
Erscheinungsjahr 2027
ISBN: 978-3-032-33989-8
Verlag: Springer Nature Switzerland AG

Buch, Englisch, 488 Seiten, Format (B × H): 155 mm x 235 mm

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.

Zielgruppe

Graduate

Autoren/Hrsg.

Karlapalem, Kamalakar

Pisipati, Radha Krishna

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Part I: Background Technologies and Underpinnings.- 1. Database Systems.- 2. Distributed Database Systems.- 3. Data Sources and Metadata.- 4. Data Analytics and ML Systems.- Part II : Data Fabric Frameworks and Systems.- 5. Data Fabric.- 6.  Data Fabric Frameworks.- 7. Data Flows and Data Pipelines.- 8. Data Fabric Ecosystems.- 9. Performance Aspects of Data Fabric Frameworks.- Part III: Data Fabric  Solution Methodologies and Case Studies.- 10.  Data Agents and Agentic Data Fabric.- 11.  Data Fabric Semantic Layer.- 12. Perspectives on Data Systems.- 13.  Data Fabric Case Studies.

Über Autor(innen)

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.