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.
Business intelligence (BI), motivations, objectives, definitions and solutions. Data warehousing as an enabling technology for BI: architectures, techniques and methodologies of On-Line Analytical Processing (OLAP) for data analysis. Multidimensional modeling with the Dimensional Fact Model (DFM). Self-service BI platforms. Relational OLAP. What-if analysis. Laboratory exercises on OLAP, DFM and self-service BI.Data Science and Business Analytics
Database Management Systems, the relational model: relationships integrity bonds. System functions and applications portfolio, the formalities of the analysis and process model, planning and business process reengineering, business intelligence. Data warehousing: architecture, techniques of data access, conceptual models. Data mining techniques.