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 activated in the A.Y. 2021/2022
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1 module among the following (1st year: Big Data epistemology and Social research; 2nd year: Cybercrime, Data protection in business organizations, Comparative and Transnational Law & Technology)
2 courses among the following (1st year: Business analytics, Digital Marketing and market research; 2nd year: Logistics, Operations & Supply Chain, Digital transformation and IT change, Statistical methods for Business intelligence)
2 courses among the following (1st year: Complex systems and social physics, Discrete Optimization and Decision Making, 2nd year: Statistical models for Data Science, Continuous Optimization for Data Science, Network science and econophysics, Marketing research for agrifood and natural resources)
2 courses among the following (1st year: Data Visualisation, Data Security & Privacy, Statistical learning, Mining Massive Dataset, 2nd year: Machine Learning for Data Science)
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) (2020/2021)
Teaching code
4S008099
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT
Period
II semestre dal Mar 1, 2021 al Jun 11, 2021.
Learning outcomes
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
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 POPITT© (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.
Author | Title | Publishing house | Year | ISBN | Notes |
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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.