Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins

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Pubblicato in:Journal of Database Management vol. 36, no. 1 (2025), p. 1-30
Autore principale: Chui, Kwok Tai
Altri autori: Singh, Sunil K., Kumar, Sudhakar, Attar, Razaz Waheeb, Alhomoud, Ahmed, Goyal, Shivam, Arya, Varsha, Gupta, Brij B.
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100 1 |a Chui, Kwok Tai  |u Hong Kong Metropolitan University, Hong Kong, China 
245 1 |a Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins 
260 |b IGI Global  |c 2025 
513 |a Journal Article 
520 3 |a The convergence of digital twin technology and data analytics continues in the area of smart cities focusing on the comprehensive study of data analysis and its visualization. It begins by standing a foundational framework for data analytics and discussing the importance of these ideas in figuring out complex patterns, concluding, and supporting thoughtful decision-making. The article emphasizes the crucial role of data analytics for urban innovation in the context of smart cities using digital twins. The study delves into the complexities of data collection, integration challenges, and innovative solutions, underscoring the necessity of constructing a robust digital twin ecosystem with a variety of sensors and data sources with its visualization. Smart recommendations by monitoring, prescriptive, and real-time analytics are becoming essential tools for vigilant urban management for taking the best and next course of action. The article delves into predictive analytics, highlighting the synergy of data streams for a comprehensive understanding of urban dynamics. 
653 |a Visualization 
653 |a Databases 
653 |a Data collection 
653 |a Data analysis 
653 |a Twins 
653 |a Machine learning 
653 |a Cities 
653 |a Smart cities 
653 |a Data transmission 
653 |a Convergence 
653 |a Decision making 
653 |a Artificial intelligence 
653 |a Digital twins 
653 |a Innovations 
653 |a Urban areas 
653 |a Real time 
700 1 |a Singh, Sunil K.  |u Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India 
700 1 |a Kumar, Sudhakar  |u Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India 
700 1 |a Attar, Razaz Waheeb  |u Management Department, College of Business Administration, Princess Nourah bint Abdulrahman University, Saudi Arabia 
700 1 |a Alhomoud, Ahmed  |u Department of Computer Science, College of Science, Northern Border University, Arar, Saudi Arabia 
700 1 |a Goyal, Shivam  |u Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India 
700 1 |a Arya, Varsha  |u Hong Kong Metropolitan University, Hong Kong, China & UCRD, Chandigarh University, Chandigarh, India, & Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, India 
700 1 |a Gupta, Brij B.  |u Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan, & Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan, & Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India, & School of Cybersecurity, Korea University, Seoul, South Korea 
773 0 |t Journal of Database Management  |g vol. 36, no. 1 (2025), p. 1-30 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3255275730/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3255275730/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch