This book is a collection of the high-quality research articles presented at the International Conference on Business Intelligence and Data Analytics (BIDA 2026), organized by RV Institute of Management (RVIM), Bengaluru, India, during April 2026. This book covers state-of-the-art research articles from the researchers and practitioners working in the field of business intelligence, data analytics, decision support systems, data warehousing and data mining, big data analytics, predictive and prescriptive analytics, and machine learning for business applications and their real-world applications.

Presents research works in the field of business intelligence and data analytics Provides original works presented at BIDA 2026 held in Bengaluru, India Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Dr. Abhishek Verma is an Assistant Professor in the Department of Management at BITS Pilani Pilani Campus. Before joining BITS Pilani, he was with the Indian Institute of Management Rohtak for over four years, where he worked in the Management Information Systems area. At IIM Rohtak, he led several executive management development programmes (eMDPs) in Data Analytics and held significant administrative positions such as Area chairperson and Programme chairperson for both long- and short-duration programmes. He holds a Ph.D. from the Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur. His research focuses on data analytics, particularly analysing large-scale textual and categorical data using data mining and machine learning techniques. Dr. Verma has published extensively in reputed international journals, including Safety Science, Enterprise Information Systems, Computers & Industrial Engineering, International Journal of Injury Control and Safety Promotion, and Process Safety and Environmental Protection. He has also authored several book chapters, conference papers, and business case studies and has presented his research at leading international conferences in India and abroad. In addition, he has served as the editor for the proceedings of two international conferences. He is a reviewer for journals such as Safety Science, Computers & Industrial Engineering, Management Review Quarterly, and Enterprise Information Systems.

Dr. Justin Zhang is an Associate Professor of Management Information Systems and Business Analytics in the Department of Management at Coggin College of Business, University of North Florida (UNF). He is also the Program Director of the Master of Science in Business Analytics (MSBA) program at UNF. He received his Ph.D. in Business Administration with a concentration on Management Science and Information Systems from Pennsylvania State University, University Park. His research interests include economics of information systems, knowledge management, electronic business, business process management, information security, and social networking. He is the editor-in-chief of the Journal of Global Information Management, an ABET program evaluator, and an IEEE senior member. His areas of Expertise are Business Analytics, Economics Of Information Systems, Information Security, Knowledge Management, Social Media. He did Master in Economics from Shanghai University of Finance and Economics, Shanghai, China and Bachelor of Engineering from Tongji University, Shanghai, China. He has received award of Excellence, 14th Scholars Transforming Academic Research Symposium, April 17, 2023, UNF and listed in Top 2% Most-Cited Scientists Worldwide 2023, 2024, 2025. He is editor in chief of Journal of Global Information Management (ABDC-A, ABS-2, SSCI, 2022 IF: 4.7, JCR Q2). He is member of various academic societies like IEEE, AIS, ACM, INFORMS.

Dr. Avinash Chandra Pandey is an Associate Professor in the Department of Cyber Security and Digital Forensics at the National Forensic Sciences University, Dharwad Campus, India. He specializes in Artificial Intelligence, Machine Learning, and Data Science applications across interdisciplinary domains, with research interests in Machine Learning, Natural Language Processing, and nature-inspired computing. With over a decade of teaching and research experience at UG and PG levels, he has published 50+ papers in reputed international journals and conferences, holds 4 patents, and has completed 2 sponsored research projects. Dr. Pandey currently supervises 3 Ph.D., 1 M.Tech, and numerous B.Tech projects and has previously guided 4 M.Tech and 30 B.Tech projects to completion. He serves as a reviewer for government-funded projects and leading international journals and is a sought-after resource person, delivering invited lectures at national and international conferences, STTPs, and QIP programs.

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When Climate Patterns Don't Stay Still: Evidence from NDVI-Based Forecasts of Irrigation Water Demand in Semi-Arid India.- Hybrid Extended Honey Badger Optimization Algorithm for Multilevel Image Segmentation.- Agentic AI for B2B Lead Acquisition: A Hybrid Scoring and CRM Integration Framework.- Unsupervised Log-Based Threat Detection using Isolation Forest and Autoencoder Ensembles.- 3Dexter: An End-to-End Pipeline for Text-to-Generative 3D Modeling and Additive Manufacturing.- Smart Pension Distribution via Machine Learning-Driven Eligibility Verification and Fraud Detection.- Conditional Retrieval Augmented Generation for Low Latency Code Completion.- A Hybrid ELM-GRU-Attention Framework for Multimodal Human Activity Recognition in Personal Healthcare Monitoring.- Training Neural Networks for Concept Drift Detection and Localization in Process Mining: Control-Flow Perspective.- Comparative Perspectives on Prompt Optimization for Large Language Models: A Comprehensive Survey.- Edge-Cloud Hybrid Architectures for Low-Latency Face Detection, Tracking, and Identification: A Comprehensive Survey.- Explainable Brain Tumor Detection Using Efficientnetb0 and Grad-Cam on Mri Images.- Custom 1D CNN Architecture for Traffic Flow Severity Classification: A Comparative Study of Machine Learning and Deep Learning Models.- Analysing the Influence of Acoustic Spectral Parameter on Genre Dynamics in Music Business Analytics.- A Comprehensive Review On Detecting Developmental Differences in Pregnancy using Transcriptomic Data.- Etc.