This book addresses the emerging area of cloud computing, providing a comprehensive overview of the research areas, recent work and open research problems. The move to cloud computing is no longer merely a topic of discussion; it has become a core competency that every modern business needs to embrace and excel at. It has changed the way enterprise and internet computing is viewed, and this success story is the result of the long-term efforts of computing research community around the globe. It is predicted that by 2026 more than two-thirds of all enterprises across the globe will be entirely run in cloud. These predictions have led to huge levels of funding for research and development in cloud computing and related technologies. Accordingly, universities across the globe have incorporated cloud computing and its related technologies in their curriculum, and information technology (IT) organizations are accelerating their skill-set evolution in order to be better prepared to manage emerging technologies and public expectations of the cloud, such as new services.

This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.

This book constitutes the refereed proceedings of the 7th International Conference on Big Data analytics, BDA 2019, held in Ahmedabad, India, in December 2019.The 25 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical and agricultural domains; graph analytics; pattern mining; and machine learning.

This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.