Description

Book Synopsis
Data Science and Analytics explores the solutions to problems in society, environment and in industry. With the increase in the availability of data, analytics has now become a major element in both the top line and the bottom line of any organization. This book explores perspectives on how big data and business analytics are increasingly essential in better decision making.
This edited work 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. Data Science and Analytics brings together researchers, engineers and practitioners to encompass a wide and diverse range of topics in a wide range of fields.
The book will provide unique insights to researchers, academics and data scientists from a variety of disciplines interested in analyzing and application of big data analytics, as well as data analysts, students and scholars pursuing advanced study in big data.

Table of Contents
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

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    A Hardback by Sneha Kumari, K.K. Tripathy, Dr. Vidya Kumbhar

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      Publisher: Emerald Publishing Limited
      Publication Date: 04/12/2020
      ISBN13: 9781800438774, 978-1800438774
      ISBN10: 180043877X

      Description

      Book Synopsis
      Data Science and Analytics explores the solutions to problems in society, environment and in industry. With the increase in the availability of data, analytics has now become a major element in both the top line and the bottom line of any organization. This book explores perspectives on how big data and business analytics are increasingly essential in better decision making.
      This edited work 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. Data Science and Analytics brings together researchers, engineers and practitioners to encompass a wide and diverse range of topics in a wide range of fields.
      The book will provide unique insights to researchers, academics and data scientists from a variety of disciplines interested in analyzing and application of big data analytics, as well as data analysts, students and scholars pursuing advanced study in big data.

      Table of Contents
      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

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