Аңдатпа
In the context of digitalization in education and increasing demands for evidence-based decision-making, the tools of educational analytics have gained particular importance. This study investigated the influence of academic data, visualized through Power BI, on managerial decisions. The unit of analysis comprised educational programs, with aggregated data on student performance metrics across three levels of training: undergraduate, internship, and residency. The sample included approximately 1,900 students from the NAO ‘Astana Medical University’ (Kazakhstan). A study was conducted integrating quantitative analysis of academic performance with a qualitative examination of managerial decision-making related to educational programs. Data sources included Power BI analytical dashboards, administrative documentation, and semi-structured interviews with university administrators (n = 6). The objective was to trace the relationship between academic metrics and managerial interventions. The results demonstrated positive trends: the proportion of students with unsatisfactory grades decreased from 6.76% (2024) to 1.27% (2025), while the share of high-achieving students increased from 26.14% to 29.54%. The most effective departments were those with an established culture of data-driven decision-making. Managerial measures included curriculum revisions, adjustments to teaching workloads, and personnel-related decisions. Educational analytics serves not only as a technical tool but also as a social mechanism for transforming institutional practices. Power BI functions not merely as a monitoring instrument but as an autonomous agent within managerial discourse, initiating shifts in the logic of educational design. Prospective research directions include analyzing institutional resistance to analytical practices and examining the readiness of administrators for data-driven decision-making.