A REVIEW OF UTILIZING NATURAL LANGUAGE PROCESSING AND AI FOR ADVANCED DATA VISUALIZATION IN REAL-TIME ANALYTICS

Abstract

This review explores the integration of Natural Language Processing (NLP) and Artificial Intelligence (AI) in enhancing data visualization for real-time analytics. In an era characterized by the exponential growth of data, traditional static visualizations are increasingly inadequate for meeting the demands of real-time decision-making. NLP and AI offer sophisticated tools to dynamically interpret and visualize data, turning vast amounts of raw information into actionable insights across various domains. This paper synthesizes current research, methodologies, and applications of NLP and AI in data visualization, highlighting key advancements such as enhanced data interpretability, real-time data processing capabilities, and improved user interaction through natural language queries and interactive elements. It also addresses the challenges and limitations associated with implementing these technologies, including computational complexity, data quality issues, and ethical considerations. The review identifies significant trends and future directions, such as the integration of augmented and virtual reality (AR/VR) and the use of generative AI models, which promise to further advance the field. By providing a comprehensive overview of the current state of NLP and AI in data visualization, this paper aims to inform and guide future research and development efforts in leveraging these technologies for more effective and efficient data-driven decision-making.