Bridging Business Intelligence and AI for Advanced Educational Data Analytics

Abstract

The increasing complexity of educational data and the imperative for data-driven decision-making within academic institutions underscore the necessity for advanced analytical tools. This study introduces the Comprehensive Educational Analysis Suite (EDUVISION), a robust platform designed to efficiently integrate, process, and analyze institutional data. Utilizing a multi-tenant architecture and AI-driven insights, EDUVISION facilitates seamless data visualization, predictive analytics, and role-based access, ensuring secure and informed decision-making. The platform harnesses machine learning, business intelligence tools, and real-time analytics to automate reporting, identify trends, and enhance institutional performance. Validation of EDUVISION was achieved through real-world implementation in a higher education environment, illustrating its effectiveness in improving strategic planning and administrative efficiency. A comparative analysis with existing frameworks underscores EDUVISION's scalability, accuracy, and usability advantages. This research contributes to the evolving field of educational data analytics, presenting an innovative solution to bridge the gap between raw data and actionable insights in academic institutions.