Full Professor of Information Processing Systems University of Bologna Core Faculty
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Golfarelli is full professor at the University of Bologna-Department of Computer Science and Engineering. Golfarelli teaches in the area of data handling and data analysis. He is interested in all the topics related to extracting information and innovating through data. He coordinates the International Master Degree in Digital Transformation Management at University of Bologna. He teaches in several masters at Bologna Business School on topics related to data handling and analysis. He has been member of the scientific board at CesenaLab:a Startup incubator in Cesena. He collaborates with several companies to realize and supervise innovative projects in the fields of Business Intelligence and Big Data.


The course presents the world of Business Intelligence and its most recent variations. The course aims to illustrate on one hand the opportunities and competitive advantages that Data Driven decisions entail in the company, on the other it introduces the problems and risks that a Business Intelligence project entails presenting basic elements related to methodologies and techniques. Organizational and technical issues (architectures, methodologies, techniques) will be complemented by the analysis of case studies and lab activities.

Executive MBA English edition

Nowadays, knowing the opinion of the media about your enterprise or a certain topic represents an important competitive edge.
The module introduces techniques, methodologies and software used in these kinds of projects. The main topics covered are:

  • Introduction to the systems of Social Media Monitoring and Social Business Intelligence
  • Architectures, techniques and methodologies for the systems of Social Business Intelligence
  • Social networks
  • Social Media Monitoring: laboratory with Brandwatch

The large amount of data produced by sensors are a valuable asset for companies. At the top level of the IoT pyramid is the transformation of such raw data into information and knowledge. Data processing in IoT has its own complexities related to data streams ingestion, data storing and analysis and requires specific technologies and approaches. This course analyses the various types of data involved, technical access to information, methods to handle them and the architectures and tools to store and process them. Furthermore, it studies data analysis and machine learning techniques to extract as more information as possible from the raw data.