THE INTEGRATION OF MATHEMATICS AND TECHNOLOGY IN DATA-DRIVEN DECISION MAKING: A LITERATURE REVIEW
Keywords:
Mathematics, Artificial Intelligence, Big Data Analytics, Data-Driven Decision Making, Digital Transformation.Abstract
Advances in digital technology have driven the transformation of decision-making from an intuition-based approach to a data-driven approach. The use of Artificial Intelligence (AI), Big Data Analytics, and predictive analytics is increasingly widespread across various sectors; however, most research still examines these technologies separately and has not yet fully integrated the role of mathematics as the conceptual foundation supporting the data-driven decision-making process. Therefore, this study aims to analyze the contributions of mathematics and technology in supporting sound decision-making through a synthesis of various recent studies. The study employs a literature review method by examining scientific journal articles, conference proceedings, and reports from international organizations published between 2021 and 2026. The literature was obtained through a systematic search, selected based on topic relevance, and then analyzed using content analysis techniques to identify themes, research trends, and conceptual relationships. The findings indicate that the application of mathematical methods—such as statistics, probability, optimization, and machine learning—combined with AI and Big Data Analytics technologies can improve prediction accuracy, operational efficiency, risk management, and the quality of decision-making in the healthcare, education, business, finance, and government sectors. However, their implementation still faces challenges related to data quality, algorithmic bias, privacy protection, and low data literacy. The research findings emphasize that strengthening mathematical literacy, data literacy, and responsible technology governance are essential prerequisites for realizing adaptive, transparent, and sustainable decision-making systems in the era of digital transformation.
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Copyright (c) 2026 Dito Wahyu Isnanta, Eleonora Nabillah Putri, Regghina Meybella Shofaa, Tarsila Tesa Felndity (Author)
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