Bibliometric Insights into the Development of Real-Time Business Intelligence Systems
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Abstract
This study presents a comprehensive bibliometric analysis of the literature on real-time business intelligence systems, spanning publications from 1993 to 2024. The research aims to map the evolution of key themes, identify influential authors and articles, and highlight emerging trends in the field. Utilizing data from Google Scholar Database, the analysis reveals a significant focus on big data analytics, machine learning, and cloud computing as critical components of modern BI systems. The study offers practical insights for organizations looking to enhance decision-making processes through real-time data processing and analytics. It also contributes theoretically by elucidating the development of business intelligence research, identifying gaps, and suggesting future research directions. Despite its contributions, the study acknowledges limitations related to data scope and methodology, underscoring the need for further exploration to deepen understanding in this rapidly evolving field.
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