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.

Type D and Type F activities

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 Management e strategia d’impresa - Enrollment from 2025/2026
primo semestre (lauree) From 9/28/20 To 12/23/20
years Modules TAF Teacher
1° 2° Future matters D Alessandro Bucciol (Coordinator)
1° 2° Future matters D Alessandro Bucciol (Coordinator)
primo semestre (lauree magistrali) From 10/5/20 To 12/23/20
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinator)
1° 2° The fashion lab (2 ECTS) D Maria Caterina Baruffi (Coordinator)
1° 2° The fashion lab (3 ECTS) D Maria Caterina Baruffi (Coordinator)
secondo semestre (lauree) From 2/15/21 To 6/1/21
years Modules TAF Teacher
1° 2° Design and Evaluation of Economic and Social Policies D Federico Perali (Coordinator)
1° 2° Public debate and scientific writing - 2020/2021 D Martina Menon (Coordinator)
1° 2° Soft skills coaching days Vicenza (terza edizione) - 2020/2021 D Paola Signori (Coordinator)
1° 2° Wake up Italia - 2020/2021 D Sergio Noto (Coordinator)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Ciclo di video conferenze: "L’economia del Covid, Verona e l’Italia. Una pandemia che viene da lontano?" - 2020/21 D Sergio Noto (Coordinator)
1° 2° Ciclo tematico di conferenze (on-line): “Come saremo? Ripensare il mondo dopo il 2020” - 2020/21 D Federico Brunetti (Coordinator)
1° 2° Corso di lingua tedesca - livello a1 (1 cfu) - 2020 (2020/2021) D Giorgio Mion (Coordinator)
1° 2° Corso di lingua tedesca - livello a1 (3 cfu) - 2020 (2020/2021) D Giorgio Mion (Coordinator)
1° 2° Data Analysis Laboratory with R (Vicenza) D Marco Minozzo (Coordinator)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° Data Science Laboratory with SAP D Marco Minozzo (Coordinator)
1° 2° Advanced Excel Laboratory (Vicenza) D Marco Minozzo (Coordinator)
1° 2° Excel Laboratory (Vicenza) D Marco Minozzo (Coordinator)
1° 2° Marketing plan - 2020/21 D Virginia Vannucci (Coordinator)
1° 2° Programming in Matlab D Marco Minozzo (Coordinator)
1° 2° Programming in SAS D Marco Minozzo (Coordinator)
Integrated Financial Planning - 2020/21 D Riccardo Stacchezzini (Coordinator)

Teaching code

4S008099

Academic staff

Alessandro Zardini,

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT

Period

secondo semestre (lauree magistrali) dal Mar 1, 2021 al Jun 1, 2021.

Learning outcomes

This course aims to introduce students to the concept and techniques of Business Analytics models, but also the new role of the "Business Analyst" within the organization. Particularly in the first part of this course, it will be used the POPIT(TM) model. Therefore, the data analysis and the interpretation of the information must always be aligned with: human resources (skills), the organizational environment, processes, and technologies. Taking as a reference the KPIs (Key Process Indicators), deriving from the business processes previously defined through the BPMN language, they will be analyzed and evaluated in real-time to create reports or dashboards to support the decision-making process. The data in addition to being used for the decision-making process, for the operational part, will also be used to align the POPIT(TM) components with the corporate business model better. This analysis will be conducted through the use of Business Intelligence tools to better respond to market needs. In the second part of the course, starting from historical series and external destructured data (through Big Data) we will proceed with the realization of predictive models to support managers in their strategic and operational decisions.

Program

The course aims to provide students with the fundamental concepts for reading, and to analyze enterprise data, to generate predictive models to support the decision-making process. The contents of the course can be summarized as follows:
1. Business Process Management, and the model POPITTM (People, Organization, Process, e IT).
2. Business Process Mapping, Analysis, and re-Engineering.
3. BPMN (Business Process Model Notation) for business integration.
4. DataWare House.
5. Business Intelligence tools.
6. Data analysis (querying, reporting, clustering, etc.).
7. Predictive Analysis (correlation, supervised regressions, etc.).
8. Introduction to Big Data.
9. People analytics.

Reference texts
Author Title Publishing house Year ISBN Notes
Davenport T.H., Harris G.J. Competere con gli analytics. La nuova scienza per vincere nel business (Edizione 1) Franco Angeli edizioni 2019 9788891781086

Examination Methods

The final test is written. Mainly, it is composed of 3 open questions.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE