Course presentation (Academic year 2023-2024)

Objectives

New technologies such as Internet of Things, blockchain and artificial intelligence have boosted the digital transformation of organisations and enabled a radical change in the provision of services deeply changing the related business models. At the same time digital technologies generate massive amounts of data and, as business and IT experts know, managing the resulting information is a growing challenge. There's a need to build out IT systems and innovative ecosystems that use data and information to create more efficient processes. However, many organisations are falling behind the curve, or haven't taken significant steps to address information management requirements. 

The aim of this course is twofold:

• to provide students and practitioners with the basic knowledge for understanding the complexity of the challenges proposed by new digital technologies and introduce the tools for managing data coming from the business environment.

• to introduce the students to the concepts of innovation and digital entrepreneurship. The module will benefit of the contributions coming from managers, researchers and innovators in order to raise the awareness regarding the disruptive nature of technological developments and develop the skills required to drive the transformation within enterprises.

Programme

Part 1 – Technologies

• • Introduction to information theory and data management

  • A brief (and incomplete) history of computing and data science

  • Data transmission networks

  • Cloud computing

  • Cybersecurity

  • Digital ledger technologies

  • Immersive technologies

  • Artificial intelligence

  • Internet of things, cyberphisical systems and smart production

  • Digital transformation and smart city development

  • Smart transport

Part 2 – Tools

• • Introduction to Excel for data management

  • Basic concepts of data analysis and visualisation

  • Excel and Matlab for data analysis

  • Project and scientific data management

Part 3 – Digital Entrepreneurship 

• • Digitally driven business strategies

  • Digitization in different industries: financial services, healthcare, production, public services 

  • Case studies

Course learning outcomes

On completion of this course the students will: 

• • Be aware of the opportunities, challenges and risks generated from digital technologies and cyber physical systems.

  • Recognise the importance of good practice in managing data in general and apply it within their own work context. 

  • Apply knowledge gained to be able to draw up a  research paper and a technology venture plan. 

  • Be able to use  data management tool such as Excel and Matlab. 

Exams

The evaluation is based on:

1. Practical exam on Part 2 of the course programme; material available on Google classroom (10%). This part is not mandatory but allows to aspire to obtain the maximum grade; without the maximum grade obtainable is 27.

2. Oral exam on Part 1 of the course programme; book and material available on Google classroom (50%).

3. Presentation and discussion of a project work (a research paper or a technology venture plan) that shows the use and the knowledge of the course topics and tools (40%). Prof. Bellini can reject the content of the paper if not in line with course program. Students have to submit the project work proposal by filling the form here within 30 days before the expected exam date. Papers must be delivered  at least 5 days before the exam date. Check on the news the info about the project work presentation.

Registration at the exams via InfoStud is mandatory.

Tutoring

At the end of the lesson during the teaching semester or by appointment.

Teaching material

• Textbook "Digital transformation and data management" Francesco Bellini, Fabrizio D’Ascenzo (edited by) - Pacini Editore 2020

• Lesson slides

• Bibliography for each lessons

• more to come...(material and news will be available for registered students on Google Classroom)

Lessons

• Monday from 10:00 to 12:00 - Room Labinfo mezzanine floor Faculty of Economics (RM019)

• Tuesday from 16:00 to 18:00 - Room 11 - Faculty of Economics (RM019)

• Wednesday from 12:00 to 14:00 - Room 11 - Faculty of Economics (RM019)