Data Quilting

An Agentic AI Framework for Constructing Explanations from Multiple Forms of Data
Erscheinungsjahr 2026
ISBN: 978-3-032-36563-7
Verlag: Springer

Buch, Englisch, 250 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Advances in Analytics and Data Science

This book presents a framework for integrating multiple forms of data to construct meaningful analytical interpretations. Organizations make important decisions by interpreting information from many sources, including numerical data, documents, conversations, images, video, and social networks. Each offers a different perspective, yet bringing these perspectives together into a coherent understanding remains one of the most difficult challenges in analytics.

Inspired by quilt making, which combines individual pieces into a unified whole, the framework preserves the contribution of each modality while revealing insights that would be difficult to obtain from any single source. Human judgment remains central throughout the process, supported by specialized AI agents that interpret individual modalities before their findings are brought together.

The book introduces the principles of data quilting before describing its agentic architecture and the responsibilities of the individual agents. Chapters examine how numerical, textual, speech, motion, social network, and music data contribute complementary perspectives on the same problem. The final chapters demonstrate how these perspectives are combined through complete worked examples that illustrate the framework in practice.

Drawing on ideas from artificial intelligence, analytics, and managerial decision making, provides researchers, graduate students, and analytics professionals with a practical approach for interpreting complex organizational problems through multiple forms of evidence.

Zielgruppe

Research

Autoren/Hrsg.

Anandarajan, Murugan

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik Mathematik Stochastik
• Wirtschaftswissenschaften Wirtschaftswissenschaften Wirtschaftswissenschaften: Allgemeines
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

1 Introduction to Data Quilting.- 2 Framing the Question: The Backing of the Data Quilt.- 3 Agentic AI as the Analytical Engine of Data Quilting.- 4 Quantitative Signals: Interpreting Numeric Data in Data Quilting.- 5 Text as Signal: Interpreting Language in Data Quilting.- 6 Speech as Signal: Extracting Behavioral Insight from Voice.- 7 Motion as Signal: Extracting Behavioral Insights from Movement.- 8 Relational Signals: Interpreting Social Networks in Data Quilting.- 9 Music as Signal: Extracting Behavioral Insight from Sound.- 10 Constructing the Quilt: From Interpretation to Explanation.- Appendix A Conducting a Data Quilting Analysis.- Appendix B Technical Implementation of the Data Quilting Framework.- Appendix C Data Quilting Vocabulary.

Über Autor(innen)

Murugan Anandarajan is Professor of Management Information Systems at Drexel University. His research focuses on artificial intelligence, analytics, and the use of structured and unstructured data to support managerial decision making. His work has been published in leading journals, including , , and . He has authored and co-authored multiple books on analytics, digital transformation, and information systems. His research has also been featured in the popular press, including and .