Utilization of Big Data Analytics in Strategic Decision Making in the Education Sector

Abstract

The rapid digitalization of education systems has generated an unprecedented volume, velocity, and variety of data, ranging from student academic records and learning management system logs to administrative and financial information. While this data abundance offers substantial potential for evidence-based governance, it simultaneously poses serious challenges for policymakers in extracting accurate, timely, and actionable insights to support strategic planning. Conventional decision-making approaches in education are often reactive, fragmented, and insufficiently responsive to the complexity of contemporary educational dynamics. This study aims to examine the utilization of big data analytics as an evidence-based approach to strengthen strategic decision-making in the education sector. A systematic literature review was conducted, complemented by a comparative analysis of big data analytics implementation across educational institutions in various countries, encompassing differences in technological infrastructure, institutional readiness, and policy contexts. The findings indicate that the application of big data analytics significantly enhances the accuracy of education policy formulation, optimizes the allocation of human, financial, and infrastructural resources, and strengthens predictive capabilities regarding student learning outcomes, including early identification of at-risk students. Furthermore, the integration of analytics-driven approaches facilitates more responsive and adaptive policy adjustments. These findings imply that the systematic adoption of big data analytics in education governance has the potential to serve as a foundational pillar for a more adaptive, efficient, and comprehensively data-driven transformation of education policy, while also highlighting the need for stronger data governance frameworks and analytical capacity building among educational institutions.