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 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 to provide to students and practitioners 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.
Part 1 – Technologies
Infrastructures and telecommunication networks
Information security
Internet of Things and cyber physical systems
Artificial intelligence and robotics
Blockchain
Part 2 – Tools
Big Data analytics
Business Intelligence
Data Mining
Machine learning
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 data management plan and maintain it throughout the project life.
Be able to organise and document data efficiently during the course of their project.
Be aware of the options available to them to securely store and back up their data.
Be able to use Excel and Python for data handling.
The evaluation is based on:
Oral exam on the course programme and material available on the website (50%).
Presentation and discussion of a project work that shows the use and the knowledge of the course topics (50%). Prof. Bellini can reject the content of the paper if not in line with course program. Students can submit the project work proposal by filling the form here. Papers must be delivered at least 5 days before the exam date.
Registration via InfoStud is mandatory.
At the end of the lesson during the teaching semester or by appointment.
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 is available for registered students on Google Drive)
Monday from 09:00 to 11:00 - Room Labinfo mezzanine floor Faculty of Economics
Wednesday from 09:00 to 11:00 - Room DidaLab 1st floor Faculty of Economics
Thursday from 09:00 to 11:00 - Room Labinfo mezzanine floor Faculty of Economics