Big Data Analysis in Management Information Systems for Financial Decision Making: A Systematic Literature Review - Trisa Afrilia Friyadi; Arjuna Rizaldi; Agus Riyanto; Mayar Mohammed Sabah Ali Alkaabi (Program Studi Keuangan & Perbankan, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia, 2025)
The integration of Big Data Analysis into Management Information Systems (MIS) has become increasingly important in supporting financial decision-making in today’s data-driven business environment. As the volume and variety of financial data continue to grow, MIS is no longer limited to traditional reporting functions but must evolve into analytical systems that provide timely and accurate information for managerial decisions. This study explores how Big Data Analytics is integrated into MIS and examines its role in improving the quality and accuracy of financial decision-making through a Systematic Literature Review (SLR) based on the PRISMA guidelines. Peer-reviewed journal articles published between 2020 and 2025 were reviewed to identify research trends, main findings, and research gaps. The findings show that Big Data Analytics enhances MIS by improving information quality, speeding up data processing, and enabling the integration of data from multiple sources, which supports more effective financial decisions. However, most existing studies still focus mainly on the technical implementation of Big Data, while the managerial integration of Big Data within the MIS framework remains limited. Therefore, this study emphasizes the importance of an integrated approach that views Big Data as a strategic element of MIS, providing a conceptual basis for developing more effective Big Data–driven financial decision-making systems and offering directions for future research related to data governance and system design. Keywords: Big Data; Management Information Systems; Financial Decision Making; SLR; Digital Transformation