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This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and…mehr
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics.
Key Features:
Comprehensive coverage of the fundamentals of big data analytics
In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems
Practical examples and case studies to help readers understand complex concepts
Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture
Discussion of challenges and legal frameworks involved in big data analytics
Clear and concise language that is easy to understand
This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.
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Keshav Kaushik is an experienced educator with over eight years of teaching and research experience in Cybersecurity, Digital Forensics, and the Internet of Things. He is working as an Assistant Professor (Senior Scale) in the systemic cluster under the School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. He has published 80+ research papers in International Journals and has presented at reputed International Conferences. He is a Certified Ethical Hacker (CEH) v11, CQI and IRCA Certified ISO/IEC 27001:2013 Lead Auditor, Quick Heal Academy Certified Cyber Security Professional (QCSP), and IBM Cybersecurity Analyst. He acted as a keynote speaker and delivered 50+ professional talks on various national and international platforms. He has edited over ten books with reputed international publishers like Springer, Taylor and Francis, IGI Global, Bentham Science, etc. He has chaired various special sessions at international conferences and also served as a reviewer in peer-reviewed journals and conferences. Prof (Dr.) Mamta Dahiya has over 21 years of experience in the academia, industry, and research. She is a Professor, Department of Computer Science & Engineering at Manav Rachna International Institute of Research & Studies, Faridabad, India. She was closely associated with research and development in the field of spatial data retrieval and related security. Building her research in Pattern Recognition, Data Science, and Information Security focusing on multiple aspects of societal problems, she has almost 85 research publications in various international and national journals of repute and conferences. She has multiple Indian and international patents granted and pub- lished. She chaired technical sessions in multiple conferences under the umbrella of Elsevier, IEEE, and TQP. She has completed multiple research projects funded by national and international agencies. She has recently completed the Consultancy on "Asian Metropolis" services to carry out the full process of research, analysis, and elaboration of the contents of the publication "Asian metropolitan report" with Metropolis, World Association of the Major Metropolises, Barcelona, Spain. Dr. Ashutosh Dhar Dwivedi is a Postdoctoral Researcher in Cybersecurity Group, Aalborg University, Copenhagen, Denmark. His research field includes Machine Learning, Cryptography, Security and Blockchain. He completed his PhD from the Polish Academy of Sciences, Poland in March 2020. He received the B.Sc. (Maths) degree from Ewing Christian College (an autonomous college of the University of Allahabad), Allahabad, India, and the MCA degree from the Amity School of Computer Sciences, Noida, India. Prior to joining Aalborg University, he worked as Postdoctoral Researcher at Department of Digitalization, Copenhagen Business School, Denmark, DTU Compute (Cyber Security Section), Technical University of Denmark, full time Visiting Researcher at the University of Waterloo, Ontario, Canada, Research Associate at the Brandon University, Manitoba, Canada, Research Employee and PhD at Polish Academy of Sciences, Warsaw, Poland and Research Scholar at the Military University of Technology, Warsaw, Poland. He has a rich industry experience as well. He was an Intern (under his master's project) with the prestigious organization "Center for Railway Information Systems, New Delhi," governed by the Ministry of Railways, India. He was with organizations related to software development projects for two years. In 2015, he moved to Poland and started a career in cryptography research.
Inhaltsangabe
1. Big Data Collection in Library for Research Purpose: Issues with Librarians in Nigeria. 2. Role of EDM and LA Techniques in Analyzing Big Data in Education System. 3. Spatial Data Analytics to Study the Pattern of Water Bodies over the Time & Possibilities of their Revival: A Case Study of Sohna MC Water Bodies, Gurugram, India. 4. Machine learning algorithms for Big Data Analytics. 5. A Modern Approach to Sentiment Analysis in Big Data: Methods, Tools, Applications, and Open Challenges. 6. Big data Analytics, Internet of Things (IoTs) and Bio-Robotics: A budding-trio for Prospective Prevention of Plant related Emerging Disease Distribution, Monitoring and Management/Control. 7. Big Data and Health Care: Analyzing the Utility, Challenges and Legal Framework in Health Industry in India. 8. Big Data Analytics in Energy Management: From Energy Generation to Consumption. 9. Artificial Intelligence (AI) at the Edge for Smart Cities Applications. 10. Power System Load Research tool for Energy Supply Industry with Data Analytics and Visualizations. 11. Data Analytics Vis-à-Vis Agricultural Development: International Scenario & Indian Potentialities-A Techno & Managerial Context. 12. IoT and Data Analytics based smart system for precision agriculture.
1. Big Data Collection in Library for Research Purpose: Issues with Librarians in Nigeria. 2. Role of EDM and LA Techniques in Analyzing Big Data in Education System. 3. Spatial Data Analytics to Study the Pattern of Water Bodies over the Time & Possibilities of their Revival: A Case Study of Sohna MC Water Bodies, Gurugram, India. 4. Machine learning algorithms for Big Data Analytics. 5. A Modern Approach to Sentiment Analysis in Big Data: Methods, Tools, Applications, and Open Challenges. 6. Big data Analytics, Internet of Things (IoTs) and Bio-Robotics: A budding-trio for Prospective Prevention of Plant related Emerging Disease Distribution, Monitoring and Management/Control. 7. Big Data and Health Care: Analyzing the Utility, Challenges and Legal Framework in Health Industry in India. 8. Big Data Analytics in Energy Management: From Energy Generation to Consumption. 9. Artificial Intelligence (AI) at the Edge for Smart Cities Applications. 10. Power System Load Research tool for Energy Supply Industry with Data Analytics and Visualizations. 11. Data Analytics Vis-à-Vis Agricultural Development: International Scenario & Indian Potentialities-A Techno & Managerial Context. 12. IoT and Data Analytics based smart system for precision agriculture.
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