Applications of Big Data and Business Analytics

✍ Scribed by Sneha Kumari; K. K. Tripathy; Vidya Kumbhar

• Publisher: Emerald Publishing
• Year: 2020
• Tongue: English
• Leaves: 204
• Category: Library

✦ Synopsis

Applications of Big Data and Business Analytics uses advanced analytic tools to explore the solutions to problems in society, environment and industry. The chapters within bring together researchers, engineers and practitioners, encompassing a wide and diverse set of topics in almost every field. 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. With this in mind, Applications of Big Data and Business Analytics brings together researchers, engineers and practitioners, encompassing a wide and diverse set of topics in almost every field. The primary target audience of this book includes researchers, academicians and data scientists from a variety of disciplines interested in analyzing and application of big data analytics. However, this work will also be of general interest to postgraduates and undergraduates pursuing advanced study in big data.

✦ Table of Contents

FM
Half Title
Title page
Copy Right
Acknowledgments
Contents
About the Editors
Foreword
Editorial Advisory Board
Preface
5 Vs of Big Data
Why is Big Data Important?
Application of Big Data and Business Analytics
Big Data and Business Analytics for Decision-Making
Objectives
Target Audience
Organization of the Book
References
Chapter 1: Data Analytics for Soil Health Management and Their Crop Mapping
Background
Introduction
Literature Review
Importance of Soil Parameters for Crop Yield
Soil Chemical Properties
Soil Fertility Parameters
Soil Physical Properties
Research Objective and Scope
Research Methodology
Result and Discussion
Comparative Study of Soil Properties for the Years 2015–2016 and 2018–2019
OC. Fig. 1 shows that the OC has improved in 2018–2019 over 2015–2016. The OC was very low in 2015–2016, which has improved over the last three years.
Nitrogen. Fig. 2 shows that the nitrogen content has also improved significantly in the current year as compared with the past. However, the soil is still not self-sufficient in nitrogen content. Nitrogen status of soil has been improved significantly.
Phosphorous. Fig. 3 shows that the soil has significantly become rich in phosphorous as compared with the past years.
Potassium. Fig. 4 depicts that the potassium level has also increased significantly in the soil.
Sulfur. Fig. 5 shows that the soil is deficient in sulfur content and not much improvement has been seen by the soil in the past three years. It has been observed that the sulfur content of the soil has deteriorated compared to the past three years. Sulfu
Zinc. Fig. 6 shows that the soil is not self-sufficient in the presence of zinc. Zinc is involved in fruit, seed, and root development. Zinc availability to crops declines with an increase in the pH of the soil, low soil temperatures, and low organic matt
Iron. Fig. 7 shows that the soil has deteriorated in iron content.
Copper. Soil is self-sufficient in copper as demonstrated in Fig. 8.
Manganese. Fig. 8 depicts that soil has shown improvement in the manganese content.
Boron. Fig. 10 shows that the soil has significantly improved the boron content.
Mapping of Soil Parameters With Crops
Cropping Pattern of Satara District
Soil Parameters Required for the Cropping Pattern
Fertilizers Mapping Based on the Status of Nutrients in 2018–2019
Possible Causes for Low Yield
Remedial Measures for Low Nutrient Content
Conclusion
Chapter 2: Analytics in Metal Sustainability: Recovery of Non-renewable Resources Using Low-cost Biomaterials
Introduction
Case Study # No. 1
Methodology
Results and Interpretation
Case Study No. 2
Methodology For Extraction of Precious Silver Metal from E-Waste Using Three-tier Combined Processes
Results, Interpretation, and Model Description
Conclusion
Chapter 3: Use of Business Analytics and GIS for Dematerialization of Land Bank in India and its Benefits
Introduction
Land Bank Distribution Pattern in India
Problems Associated with Current Land Titles
Geographical Information System (GIS) and its Evolution
Evolution of GIS
Creating a GIS Data System
Other Applications of GIS
Geographic Research. GIS can be used in a number of ways for carrying out geographical research. Its foundation lies in spatial analysis and decision-making and digitalization of the spatial information. It can help in identifying the distance between cit
Mobility and Health Care. GIS is useful in analyzing, monitoring, and restricting mobility. It can be used effectively in solving traffic issues and access to health care services (Dummer, 2003; Dummer & Parker, 2003; Jones, Bentham, & Horwell, 1999; Love
Logistics. GIS is also used to smoothen the logistics hurdles. Through GIS, an analysis of the route can be done that will help in identifying whether the route is appropriate, traffic, and weather conditions to identify and mitigate the reasons of unexpe
Land Digitization and GIS. Land digitization is a process of converting land bank into electronic form. The original maps can be in the form of survey of India maps or from aerial survey. When surveyed maps are used for digitization, the process is common
Land Digitization Initiative by Central and State Governments in India
Conceptual Framework for Dematerialization of Land and Use of Data Analytics
Proposed Policy for Implementation
Applications/Advantages Associated with Dematerialization of Land Bank in India
Short-term Problems/Special Efforts Needed for Dematerialization of Land Banks
Applications Associated with Business Analytics
Conclusion
Further Research Directions
Chapter 4: Using Google Trends in Modeling Product Demand and Consumption: Case of UK Apparel and Footwear Demand
Introduction
Previous Related Research
Methodology
ARMA Models
VAR Models
Empirical Results
Variable Description
ARMA Modeling Results
VAR Modeling Results
Discussion
Conclusion
Chapter 5: Applications of Big Data Analytics: A Boon for the Food Industry
Introduction
Background
Business Segments that Use Big Data
Applications of Big Data in Fruits and Vegetable Sector
Onion Scenario
Domestic Demand and Consumption
Working Capital Analytics
Inventory Analytics
Human Resource Planning and Workforce Analytics
Risk Analytics
Jain Farm Fresh
Possible Approaches for Reducing Post-Harvest Losses
Proposed Innovation in Food Industry
Conclusion
References
Websites
Chapter 6: Importance of Data Analytics in International Trade: A Case of Indian Cotton
Introduction
Background
Methodology
Findings and Discussion
Future Research Directions
Conclusion
Chapter 7: Data Management in India: A Case Study of Aadhaar Project
Introduction
Review of Literature
Research Objectives
Understanding Aadhaar
Chronology of Aadhaar
Aadhaar Scheme (2014–2018)
Understanding Aadhaar (Targeted Delivery of Financial and Other Subsidies, Benefits and Services) Act 2016
Benefits of Aadhaar Scheme
Benefits of AADHAAR to Government
Benefits of Aadhaar to Individuals
Challenges to Aadhaar
Privacy and Surveillance
Absence of Clear Redressal Mechanisms for Consumers in Case of a Data Leak, Misuse, or Hack
Mandatory Versus Voluntary
Linking of Aadhaar with PAN
Money Bill
K. S. Puttaswamy v. Union of India: An Overview of the Aadhaar Judgment
Majority Opinion
Minority Judgment
Conclusion
Chapter 8: Customer Segmentation Using RFM Analysis: Real Case Application on a Fuel Company
Introduction
Literature Review
Customer Segmentation
Methodology
Application: Customer Segmentatıon on a Fuel Company
Reward and Invest
Information About The Company
RFM
Data
Customer Demographic Information.
Annual Loyalty Card Utilization Rates
Modeling the Data
Solutions and Recommendations
Key Terms and Definitions
References
Index