Stefano
Rizzi


Rizzi
Italy Full Professor of Information Processing Systems University of Bologna Core Faculty
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Stefano Rizzi received his Ph.D. in 1996 from the University of Bologna, Italy. Since 2005 he is Full Professor at the University of Bologna, and since 2015 he is the director of the Bologna unit of CINI (Consorzio Interuniversitario Nazionale per l’Informatica). Since 2013 he is member of the Computer Science PhD board at the University of Bologna. He has published more than 150 papers in international refereed journals and conferences mainly in the fields of data warehousing, business intelligence, and pattern recognition, and a research book on data warehouse design. He is member of the steering committee of DOLAP since 2004, and has been member of the steering committee of ER from 2012 to 2015. In 2020 he was appointed ER Fellow from the ER steering committee. Since 2014 he is part of the editorial board of the Data & Knowledge Engineering Journal (Elsevier). He participated in the H2020-ICT-2015 TOREADOR project and in several national research projects contracts with companies. He has also been a consultant for several companies (e.g., Yoox, Ragioneria Generale dello Stato, Montenegro, Regione Emilia Romagna, FCA), mainly with reference to business intelligence, and since 2002 he is scientifical supervisor of the “University Data Warehouse Project” at the University of Bologna. His current research interests include data warehouse design and business intelligence, in particular OLAP on NoSQL data, social business intelligence, and analysis services for big data.

COURSES

The goal of the course is to introduce business intelligence (BI) platforms, with specific reference to data warehouses seen as an enabling technology for BI. Teaching will be mainly focused on OLAP, multidimensional modelling (at both the conceptual and logical level), and self-service BI. Some notions about data integration and cleaning will be provided.

Data Science and Business Analytics
  • Business Intelligence
  • Data Warehouse: process and architectures
  • Multidimensional modelling and OLAP
  • The Data Warehouse Systems Development Cycle
Data Strategy & Analytics