This research paper presents a comprehensive data analysis of study fields, employment, and salaries, containing information on academic majors, employment rates, gender distributions, and salary metrics. The study explores the relationship between academic disciplines and employment outcomes using techniques such as data cleaning, preprocessing, exploratory data analysis (EDA), and visualization. Key metrics, including employment rates, full-time employment rates, unemployment rates, and median salaries, were computed and compared across major categories. For instance, the analysis revealed that engineering majors exhibit an 83% full-time employment rate and command the highest median salaries, while arts majors show a full-time employment rate of just 63% with significantly lower earnings. By employing visualizations like heatmaps, scatter plots, and bar plots, the study provides a detailed understanding of employment trends. These findings highlight substantial variations in employment outcomes by field of study. This analysis offers valuable insights to students, educators, and policymakers, enabling them to align educational pathways with labor market needs. The results emphasize the importance of STEM and technical fields, which offer stronger job prospects and financial rewards, compared to fields such as arts and humanities. Challenges such as missing data and multicollinearity were also addressed, ensuring the robustness of the findings.