Journal of Information Systems Engineering and Management

Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology
Jinze Li 1 2 *
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1 Doctor of Philosophy in Business Management, Lyceum of the Philippines University (Manila Campus), Manila, Philippines
2 Hubei Media Group, Wuhan, China
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2024 - Volume 9 Issue 2, Article No: 24148
https://doi.org/10.55267/iadt.07.14747

Published Online: 24 Apr 2024

Views: 296 | Downloads: 135

How to cite this article
APA 6th edition
In-text citation: (Li, 2024)
Reference: Li, J. (2024). Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology. Journal of Information Systems Engineering and Management, 9(2), 24148. https://doi.org/10.55267/iadt.07.14747
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Li J. Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology. J INFORM SYSTEMS ENG. 2024;9(2):24148. https://doi.org/10.55267/iadt.07.14747
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Li J. Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology. J INFORM SYSTEMS ENG. 2024;9(2), 24148. https://doi.org/10.55267/iadt.07.14747
Chicago
In-text citation: (Li, 2024)
Reference: Li, Jinze. "Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology". Journal of Information Systems Engineering and Management 2024 9 no. 2 (2024): 24148. https://doi.org/10.55267/iadt.07.14747
Harvard
In-text citation: (Li, 2024)
Reference: Li, J. (2024). Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology. Journal of Information Systems Engineering and Management, 9(2), 24148. https://doi.org/10.55267/iadt.07.14747
MLA
In-text citation: (Li, 2024)
Reference: Li, Jinze "Big Data-driven Decision Support: Enhancing Information Integration and User Experience with Mobile Integrated Technology". Journal of Information Systems Engineering and Management, vol. 9, no. 2, 2024, 24148. https://doi.org/10.55267/iadt.07.14747
ABSTRACT
This study examines how big data-driven decision support and mobile technology interact to improve information integration and user experience. The research studies big data for digital decision-making and provides theoretical and practical suggestions to assist organizations in overcoming its challenges. This study used mixed method analysis to find the relationship between big data-driven user experience and mobile-integrated technology. Businesses require sophisticated decision support tools to navigate the digital landscape of massive data. Big data-driven decision support is examined to determine how information integration and user experience affect mobile-integrated technologies. A rigorous quantitative technique examines data volume and decision precision. Although big data volumes may have diminishing returns, decision-making generally improves. The study emphasizes the delicate balance between data volume, quality, velocity, diversity, and governance. Beyond quantitative analysis, the study examines complex decision-making. Information integration methods and user experience affect decision-making time, with more data offering strategic options. Agile integration and user-centric design boost efficiency and decision-making. The research highlights the change in mobile integrated technology. The title fits the research since mobile technology increases information integration and user experience. According to the study, mobile technology's user-friendly gadgets, quick internet connectivity, security safeguards, and app functionality boost user contentment, productivity, and decision-making accuracy. The report also emphasizes big data governance in decision quality. Decision support systems need big data governance for data access, accuracy, security, and compliance. Finally, this study provides theoretical insights into big data-driven decision support and practical suggestions for organizations navigating it. The study uses data, technology, user experience, and governance to improve business decision-making. This provides them with digital-era precision, agility, and strategic edge.
KEYWORDS
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