Abstract
In today's data-driven business landscape, the analysis of big data has become a pivotal tool for making informed decisions across industries. This research method paper explores the methodologies employed in big data analysis for business decision-making and conducts a bibliometric analysis using VOSviewer to map the scholarly landscape of this field. The systematic literature review identifies key methodologies, including descriptive, predictive, and prescriptive analytics, text analysis, and network analysis. Real-world case studies demonstrate their practical applications in diverse sectors such as retail, finance, healthcare, and more. The bibliometric analysis unveils influential authors, collaborative networks, research clusters, and trends within the academic discourse on big data analysis and business decision-making. By integrating empirical research, systematic review, and bibliometric analysis, this paper offers a comprehensive understanding of the role of big data analysis in shaping contemporary business decisions.
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