The presence of women in technology-related courses is declining every year, reaching in 2016 less than 20% of the total student body in the Department of Computer Science in UnB (Universidade de Bras´ılia). This paper uses visualization techniques to analyze and identify profile patterns in girls on undergraduate courses in the computing field. Dimensionality reduction technique (PCA), HeatMap and Parallel Coordinates were used for the visual data analysis process, considering the students’ situation in relation to UnB (active, drop out or graduated). In this work, the existing correlations between variables were evidenced, with more in-depth analysis of the association between entrance period and the nature of the university departure form and period of the university attendance. Also, the students participating in the quota schema were analysed and the study suggests that there is no correlation between students enrolled under the quota system and the form of departure from the course. 
