This paper presents a comprehensive study on identifying subject correlations in secondary education through a holistic approach. Using advanced data mining techniques, including correlation, regression, factor analysis, and hierarchical clustering, we analyzed the performance data of over 600 students. The findings reveal significant patterns of subject correlations, highlighting the interconnectedness of academic disciplines. This holistic perspective suggests that traditional subject-specific analyses may miss critical influences from other areas. The study provides valuable insights for educators and policymakers, indicating that holistic approaches can lead to more effective educational strategies and improved student outcomes. Future research directions include expanding the dataset and exploring causal relationships with advanced machine learning techniques.