Italy Associate Professor of Information Elaboration Systems University of Bologna Adjunct
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Matteo Golfarelli is Associate Professor of Information Technology at the Science and Engineering Department of the University of Bologna and teaches information systems, databases and data mining. He has published over 100 papers for international journals and conferences on topics such as pattern recognition, robotics, multi-agent systems and business intelligence - his primary research sector. His current research involves distributed and semantic data warehouses as well as business intelligence on open, social and big data. He has been involved in multiple research projects, in Italy and abroad, within these areas of research. He is actively engaged in technological transfer in the business intelligence sector, liaising with public and private italian companies and has been scientific supervisor for multiple business conventions. He is member of the scientific committee for CesenaLab, a start up incubator for the digital sector.


The digital revolution has led to an explosion in the amount of available data and information (Big Data), the ability to analyze and correlate this information is becoming a fundamental element to an enterprise’s competitiveness and a new source of economic value and innovation. Big Data, however, is unable to be managed properly by using traditional instruments of Information Technologies because of their size, their heterogeneity and their many peculiarities. For this reason, new architectures, methodologies and tools are being created for data scientists to transform this data into value for the company and to support the decision-making process. This course will analyze the various types of data available, technical access to information, methods to handle them and the architectures and tools to store and process them.

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.

Many academics and practitioners see big data revolution like electrification, which changed the world and the economy.  Big data and business intelligence have become increasingly important in both the academic and the business communities over the past two decades. For example, based on a survey of over 4,000 information technology (IT) professionals from 93 countries and 25 industries, the IBM Tech Trends Report (2011) identified business analytics as one of the four major technology trends in the 2010s. The course has the goal to highlight the connection between big data and business intelligence and the impact of this relation to the business model of companies, with a specific focus on digital business.

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.

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