Application of Predictive Analytics through Big Data in Business and Educational Decision-Making

Abstract

Digital transformation has significantly increased data generation within business and educational organisations, driving the need to implement technologies capable of converting vast volumes of information into valuable knowledge for institutional management. In this context, Big Data and predictive analytics have gained increasing prominence due to their ability to identify patterns, trends and behaviours that support evidence-based decision-making. The purpose of this study was to critically and systematically examine the application of predictive analytics supported by Big Data in business and educational settings, assessing its methodological, technological and organisational contributions. The methodology was based on a documentary review supported by the PRISMA model, involving the collection, selection and analysis of specialised scientific literature related to the subject. The evidence examined indicated that the use of predictive models facilitates the anticipation of future scenarios, the identification of risks, the optimisation of resources and the strengthening of planning and management processes. Furthermore, it was found that the strategic use of data contributes to improving organisational efficiency, enhancing institutional intelligence and supporting more accurate and timely decision-making. The findings highlighted that predictive analytics powered by Big Data represents a key component for fostering innovation, competitiveness and institutional performance in environments characterised by increasing complexity and ongoing digital transformation.