Abstract

Over the years, the issue of education in Chile has persisted, directly impacting national development, particularly in terms of the quality and quantity of professionals effectively integrating into society and contributing to the country's progress. Despite significant initiatives aimed at facilitating access to higher education, these measures seem to fall short of full effectiveness. To address this challenge, publicly available data from the Ministry of Education will be utilized, employing OLAP tools to identify behavioral patterns that can inform the construction of a predictive model regarding delays in graduation processes and dropout rates in higher education. The resulting data cube will be made publicly available to the scientific community, aiming to foster collaborative efforts in tackling these educational challenges. © 2024 IEEE.