Data science and analytics / edited by Dr. Sneha Kumari (Vaikunth Mehta National Institute of Cooperative Management, India), Dr. K. K. Tripathy and Dr. Vidya Kumbhar (Symbiosis Institute of Geoinformatics, India).

Includes bibliographical references and index.

Chapter 1: Data visualization / Aarti Mehta Sharma -- Chapter 2: Analytical aspects of multimedia big data computing and future scope / Hiral R. Patel, Ajay M Patel Satyen M Parikh -- Chapter 3: Predictive analysis: comprehensive study of popular open source tools / Gauri Rajendra Virkar, Supriya Sunil Shinde -- Chapter 4: Market opportunities through effective market analytics / Shakti Ranjan Panigrahy -- Chapter 5: Stochastic point process techniques for modelling problems in IoT and marketing: technique of "Random Point Process" (RPP) & "Product density" (PD)techniques in stochastic modeling / KSS Iyer, Madhavi Damle -- Chapter 6: Real-time data analytics - a contemporary approach towards customer relationship management / Samir Yerpude -- Chapter 7: Application of big data for sustainable rural development with special reference to MNREGA / K. K. Tripathy, Sneha Kumari -- Chapter 8: Challenges of digital technologies in the development of supply chains: a guide for their selection / Jorge Tarifa-Fernandez, Almudena Martínez Aguilera, José Felipe Jiménez-Guerrero.

Data Science and Analytics explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications.

Print version record.