Two Italian teams, from the University of Padua and the University of Bologna, have won the SAS Curiosity Cup. The international competition, promoted by the analytics giant SAS, is dedicated to next generation of data scientists to explore, analyze and learn from data. Using SAS software, teams of students from around the world have researched a variety of topics, from mental health to energy, from entertainment to fraud, resulting in presentations judged by industry experts in three categories: data preparation, data analysis and data presentation.

Curiosity Cup contestants enjoyed free access to learning resources, such as SAS Viya for Learners or SAS OnDemand for Academics, or SAS software licensed by their university. Viya for Learners and OnDemand for Academics are available to all students through SAS Skill Builder for Students, a new global program that students can access 24/7 to learn analytical skills, to company- certifications and to get in touch with job opportunities.

The teams are made by two to four students with a counselor from their own faculty. The teams chose the SAS learning software, data and analysis questions for the competition. The judges evaluated the works based on the preparation, analysis and presentation of the data, as well as knowledge of the subject. The winning teams received 12 months of free access to the SAS Academy for Data Science.

The winners of the 2022 edition of the SAS Curiosity Cup are:

• Data Preparation: OverSeAS Team of the University of Padua, Italy – “Depression: Can Caregiving Be a Risk? A study on a European scale”
• Data Analysis: TheAristoSAS Team of the University of Bologna, Italy – “Two possible approaches for the DASS dataset (Depression, Anxiety and Stress)”
• Presentation of the data: Team Data Campers of the IESEG School of Management, France – “Influence of Netflix shows on European tourism”

"SAS Curiosity Cup was certainly an occasion where we grew in programming, teamwork and the ability to perform a comprehensive analysis. For the first time we had the opportunity to compare ourselves with real data and to be able to outline the analysis process in its entirety, without a specific assignment, deciding on our own the best method", said Sara Rinaldini, member of TheAristoSAS team.