Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year It will be activated in the A.Y. 2025/2026
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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1 module among the following
2 modules among the following
1 module among the following
- A.A. 2024/2025 Complex systems and social physics - Network science and econophysics - Statistical methods for business intelligence not activated
- A.A. 2025/26 Network science and econophysics not activated
1 module among the following
2 modules among the following
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Business _Analytics (BA) (2024/2025)
Teaching code
4S008099
Teacher
Coordinator
Credits
6
Also offered in courses:
- Business _Analytics (BA) of the course Master's degree in Data Science
Language
English
Scientific Disciplinary Sector (SSD)
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT
Period
Semester 2 dal Mar 3, 2025 al Jun 13, 2025.
Courses Single
Authorized
Learning objectives
This course aims to introduce students to concepts and techniques in Business Analytics, but also to the new role of the "Business Analyst" within an organization. Starting from the KPIs (Key Process Indicators), coming from the business processes defined through the BPMN language, we will proceed to the analysis and real-time evaluation of the same in order to create reports or dashboards to support the decision-making process. In addition to being used for decision-making, the data will also serve to better align the POPITTM components with the company business model.
At the end of the course the student has to show to have acquired the following skills:
- Ability to conduct business intelligence analyzes
- obtain structured information from data according to project specifications
- analyze high-level solutions to meet Detailed market needs
- Ability to use software tools and mathematical models in predictive analytics
Prerequisites and basic notions
None
Program
The course aims to provide students with fundamental concepts for reading and analyzing business data, enabling them to create predictive models to support decision-making processes. Specifically, the following topics will be covered:
Data management and Data Warehouse
Data Modeling Techniques
Data Integration Techniques
Data Platforms
Business Intelligence Tools
Historical data model and analysis
Data Quality
DataOps
Business models for predictive analytics
Bibliography
Didactic methods
In addition to the lectures during the course, space will be given to the analysis and discussion of cases developed by the students.
Furthermore, throughout the academic year, an individual reception service managed by the teacher is available, at the times indicated on the web pages (please send an email to make an appointment) and constantly updated.
Learning assessment procedures
The exam consists of a written test. Students are invited to consult the notices in Moodle. The test will consist of three open questions.
Other methods of learning assessment will also be evaluated at the discretion of the teacher.
Evaluation criteria
The questions are structured in such a way as to verify the level of knowledge of the topics concerning business analysis. At the same time, they are designed to test the ability to interpret the main issues related to problem-solving.
Criteria for the composition of the final grade
3 questions
Exam language
English