Deshwal, Priyanshi (2025) AI-driven data visualization: Enhancing user interfaces with machine learning. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 2176-2182. ISSN 2582-8266
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Abstract
AI and machine learning technologies are transforming data visualization, offering solutions to the challenge of deriving insights from increasingly complex datasets. This article explores how these technologies enhance user interfaces through automated visualization recommendations, personalized dashboards, real-time predictive analytics, and natural language interfaces. By analyzing implementation considerations across technical, design, and strategic dimensions, the article demonstrates how AI-driven visualization tools improve efficiency, accuracy, and accessibility. A case study of a financial services institution illustrates these benefits, while an exploration of future trends—including augmented analytics, multimodal interaction, embedded intelligence, and collaborative intelligence—reveals the evolving landscape of data visualization. These innovations are making analytics more intuitive and impactful, allowing organizations to process information more effectively in an era of exponential data growth.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.2.0704 |
Uncontrolled Keywords: | Augmented Analytics; Collaborative Intelligence; Data Visualization; Machine Learning; Natural Language Interface |
Depositing User: | Editor Engineering Section |
Date Deposited: | 04 Aug 2025 16:39 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/4042 |