Within the more general quality assurance pathways undertaken by the universities, inbound and on going guidance activities are assuming an increasingly strategic role with the aim to reduce the dropout rate and the time to qualification. In this contribution, the usefulness of some typical data mining solutions is evaluated in the context of students’ careers analysis. More in detail, an analysis of graduates’ careers paths is proposed, mainly based on the application and comparison of clustering procedures. With our proposal we aim at identifying career paths that are particularly virtuous in terms of average scores and time to qualification. Such type of information can be used by the university management for planning the career paths of freshmen.