Research Practitioner's Handbook on Big Data Analytics

S. Sasikala, PhD, is Associate Professor and Research Supervisor in the Department of Computer Science, IDE, and Director of Network Operation and Edusat Programs at the University of Madras, Chennai, India. With 23 years of teaching experience, she has held various posts at the university, including Head-in-charge of the Centre for Web-based Learning, Nodal Officer for the UGC Student Redressal Committee, Coordinator for Online Course Development at IDE, and President of the Alumni Association at IDE. Her research interests include imaging, data mining, machine learning, networks, big data, and AI. She has published two books on computer science and published over 27 research articles in leading journals and conference proceedings as well as four book chapters. She has also received best paper awards and women's achievement awards. She is an active reviewer and editorial member for international journals and conferences.

D. Renuka Devi, PhD, is Assistant Professor in the Department of Computer Science, Stella Maris College (Autonomous), Chennai, India. She has 12 years of teaching experience. Her research interests include data mining, machine learning, big data, and AI. She actively participates in continued learning through conferences and professional research. She has published eight research papers and a book chapter in publications from IEEE, Scopus, and Web of Science. She has also presented papers at international conferences and received best paper awards.

Raghvendra Kumar, PhD, is Associate Professor in the Computer Science and Engineering Department at GIET University, India. Dr. Kumar serves as Editor of the book series Internet of Everything: Security and Privacy and the book series Biomedical Engineering: Techniques and Applications (Apple Academic Press). He has published several research papers in international journals and conferences. He has served in many roles for international and national conferences and has authored and edited over 20 computer science books in the field of Internet of Things, data mining, biomedical engineering, big data, robotics, graph theory, and Turing machines.