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
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026The 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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4 modules among the following2° Year It will be activated in the A.Y. 2025/2026
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4 modules among the following| Modules | Credits | TAF | SSD |
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3 modules among the following2 modules among the followingLegend | 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 intelligence (2024/2025)
Teaching code
4S011697
Academic staff
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
Semester 2 dal Mar 3, 2025 al Jun 13, 2025.
Courses Single
Authorized
Learning objectives
The main aim of the course is providing students with theoretical foundations of decision support system design, data integration and data analysis techniques. In particular, techniques for decision support system design, data integration techniques and visualization and analysis of data will be described. At the end of the course the student will be able to master knowledge and skills about designing and management of a Business Intelligence System, and to understand system requirements and communicate appropriately with stakeholders. In particular, the student will be able to design and manage a decision support system, to apply data integration techniques, and analyse multidimensional data. She will also be able to autonomously continue studies in the Information Systems field.
Prerequisites and basic notions
Basic concepts of databases.
Program
- Decision support systems.
-- Data Integration.
- Data Analytics.
-- Dashboard and Data Visualization.
-- OLAP queries.
-- Classification.
--- Decision Trees.
--- Bayesian classification.
--- Association rules classification.
--- Classification accuracy.
--- Spatial Data Classification.
-- Clustering.
--- Spatial Data Classification.
--- K-means clustering and k-nn clustering.
--- Hierarchical clustering.
--- Density-based Clustering.
--- Grid-based clustering.
--- Clustering accuracy.
-- Data Mining vs. Machine Learning.
Bibliography
Didactic methods
In-person classes.
Learning assessment procedures
Written test with exercises and questions.
Evaluation criteria
To pass the exam, the students must show that:
- they have understood the concepts related to decision support systems, and data analytics;
- they are able to describe the concepts in a clear and exhaustive way;
- they are able to apply the acquired knowledge to solve application problems described by means of questions and exercises.
Criteria for the composition of the final grade
Criteria for exam evaluation:
- Mastery of contents and depth of knowledge.
- Propriety of language with respect to topics.
- Ability to solve application problems.
Exam language
Italiano
