A Comprehensive Analysis of Factors Influencing Students' Academic Performance and Job Placement using MS-Azure

This study examines the crucial role of data analysis in improving student academic performance and guiding them towards successful career paths. Recognizing that higher education institutions often collect vast amounts of student data that remains underutilized, the research emphasizes the importance of leveraging this data to gain valuable insights into student capabilities and potential. The study analyzes data from 1673 students across two districts in Tamil Nadu, employing MS-Azure ML Studio and Python to visualize and analyze key demographic variables. The research identifies counseling and mentoring as crucial interventions that significantly improve student academic performance. A positive correlation was observed between the number of counseling sessions attended and academic outcomes, highlighting the effectiveness of personalized support in addressing challenges and fostering growth. Additionally, the study found that consistent improvement in academic performance followed each mentoring session, emphasizing the value of structured guidance. The analysis of demographic data reveals significant insights into factors influencing student performance. The study uncovers a notable gender gap across different regions, indicating the need for initiatives that promote equitable access to education and resources. Parental education level emerged as a strong predictor of student achievement, suggesting that a supportive home environment with educated parents plays a vital role in educational success. Furthermore, the research demonstrates a strong link between student participation in co-curricular activities and favourable job placement outcomes. Students actively engaged in extracurricular activities were more likely to secure positions in desirable companies, emphasizing the importance of a well-rounded educational experience. This study highlights the transformative potential of data analysis in shaping educational strategies. By identifying and analyzing key demographic variables, institutions can develop targeted interventions, support systems, and counseling programs to address specific student needs and promote academic success. The findings encourage a shift towards a data-driven approach in education, empowering institutions to create a more equitable and effective learning environment that prepares students for fulfilling careers.