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

Academic year:
List of courses with unassigned period
years Modules TAF Teacher
Data discovery for business decisions D Claudio Zoli (Coordinator)
Elements of financial risk management D Claudio Zoli (Coordinator)
Introduction to business plan D Paolo Roffia (Coordinator)
Professional communication for economics (3 cfu) D Claudio Zoli (Coordinator)
Regulation, procurement and competition D Claudio Zoli (Coordinator)
SFIDE - Europe D Claudio Zoli (Coordinator)
1° 2° Advanced risk and portfolio management bootcamp (online) (3 cfu) D Roberto Reno' (Coordinator)
1° 2° Advanced risk and portfolio management bootcamp (onsite) (6 cfu) D Roberto Reno' (Coordinator)
1° 2° Convegno "gli scambi commerciali con l'estero: questioni fiscali, doganali e contrattuali" D Sebastiano Maurizio Messina (Coordinator)
1° 2° English for business and economics D Claudio Zoli (Coordinator)
1° 2° Ineka conference 2019 teamworking membership D Federico Brunetti (Coordinator)
1° 2° Introduction to spatial analysis and data visualization D Claudio Zoli (Coordinator)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° "le grandi trasformazioni degli anni '60-'70 e l'italia cinquant'anni dopo" D Angelo Zago (Coordinator)
1° 2° Social responsibility model for the restaurants' ecosystems D Silvia Cantele (Coordinator)
1° 2° Marketing Plan D Ilenia Confente (Coordinator)
1° 2° Polis - festival biblico in universita' D Giorgio Mion (Coordinator)
1° 2° Predictive analytics for business decisions D Claudio Zoli (Coordinator)
1° 2° Programming in Matlab D Diego Lubian (Coordinator)
1° 2° Programming in R D Diego Lubian (Coordinator)
1° 2° Programming in SAS D Diego Lubian (Coordinator)
1° 2° Programming Stata (3 cfu) D Diego Lubian (Coordinator)
1° 2° Quality and problem solving in business organizations D Paola Castellani (Coordinator)
1° 2° La competitività regionale e le sue risorse endogene: il concetto di capitale territoriale D Riccardo Fiorentini (Coordinator)
1° 2° Soft skills in action D Paola Signori (Coordinator)
1° 2° Tools for applied economic analysis D Claudio Zoli (Coordinator)

Teaching code

4S007982

Coordinator

Claudio Zoli

Credits

2

Also offered in courses:

Language

English en

Scientific Disciplinary Sector (SSD)

NN - -

Period

Not yet assigned

Learning outcomes

This is an optional module for the equivalent of 2 credits and 12 hrs of classes/laboratory activities. The module is coordinated with SDG Consulting Italia with the contribution of SDG experts in Business Analytics.
It will introduce students to the Corporate Performance Management landscape and aims at developing skills on Business Intelligence tools management.
It will be an opportunity for student for experiencing data analysis closely related to the main activities of a consulting company working on business analytics, Students will be involved in studies of business cases with mapping of data-intensive processes, business model analysis and assessment of business needs.
At completion of the module students should be able to:
- Understand the main tasks and information relevant for designing analytical solutions supporting business processes and decisions
- Master the main techniques for predictive analytics to support business decisions.

Program

The program includes class lecures on one of the most relevant Business Intelligence tools and its main functionalities, followed by a lab workshop (over two days) were students will simulate a business case starting from the customer needs up to the translation into a data model and the connected reporting analytics (KPI, Variances,..).
Classes will cover the subjects of:

1. Scope and methodology for Business Intelligence initiatives
2. Modelling and implementing solutions supporting business processes and decisions
3. How to Navigate Master data, Choose Metrics and Generate Insights
4. Predictive Analytics: using many techniques from datamining, statistics, modelling, machine learning, and artificial intelligence to analyse current data to make predictions about future.

5. Workshop:
a. How to analyse the dimensional context and collect data
b. Decision making: understand the situation, generate and evaluate alternatives, simulate decisions
c. Sales Analysis (by Customer, Area, Channel, Product,..)
d. Profitability calculation (by Product, Channel, Top Customers)
e. Variance Analysis (Quantity, Price, Mix)
f. Brand Performance
g. P&L Forecast and Budget simulation

Classes and labs activities will be integrated by coursework activitites based on the the elaboration and critical analysis of the material developed in lab.
Reference material will be made available during the laboratory activities.

Reference texts
Author Title Publishing house Year ISBN Notes
Piegorsch, Walter Statistical data analytics Chicester: Wiley 2015

Examination Methods

A final assessment of the coursework will be based on the evalutaion of a report submitted by students and based on the analysis of the business cases discussed in the workshop on “Multidimensional Data Analysis for Business Decision Making”. The report will have to include comments and output results from the workshop analysis as well as critical assessments of the process and will have to adress methodological questions related to the content of the module.
Attendance and a positive final assessment of the report are required in order to be entitled to the 2 credits associated with the module.

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