Harnessing Data Science for University Financial Management: Innovations and Best Practices

Abstract

Universities have been operating under the pressure of rising financial demands and hence, they are trying to find out ways and means to address this crucial area. The use of data science in decision making process is a plausible remedy to these challenges. This paper aims at examining the viability of applying data science to manage the financial perspective of universities, with the emphasis on the potential of improving the budget, and financial prediction activities, as well as in resource utilisation. These technologies include predictive model, machine learning, and data visualization that can help universities to forecast the financial trends, areas of wastage, and ways of addressing the problems. It also briefly explains the advantages of data application in revenue enhancement, costs containment, and the management of financial risks. Furthermore, it describes approaches and effective experience of the most popular universities that implemented data science in their finances. It gives good ideas on how to overcome implementation problems and thus improve the efficiency of data science in higher education finance. Finally, the study provides recommendations for universities that wish to achieve the maximum optimal usage of data science to enhance the financial management system and financial sustainability for instability in the current evolutionized education systems.