Learning objectives

The course will introduce the modeling / quantitative foundations of modern Business Analytics (BA) theory, taking advantage of a rigorous mathematical approach in order to effectively deal with real case studies. Through probabilistic / statistical tools of descriptive and predictive analysis, the course will provide elements of predictive analysis, risk analysis, simulation and data mining and decision analysis. Students will acquire the fundamental theoretical tools both to develop models to manage typical BA challenges, and to communicate their results concretely, so as to provide brilliant solutions to specific problems in a synergistic and proactive way. A great emphasis will be given to real world applications, also making use of specific packages for data analysis, manipulation and prediction (e.g. Rapidminer, Orange, Knime, R-AnalyticFlow, etc.). At the end of the course the student has to show to have acquired the following skills: ●
master the typical pipeline: query, reporting and online analytical processing ' ●
ability to control the analytical / quantitative flow, i.e. I / O data management, forecasting and optimization ●
ability to develop models in predictive analytics ●
ability to develop data mining and cluster analysis models ●
ability to classify within heterogeneous databases ●
ability to develop pro customer retention rate, targeting marketing models, also in relation to social media, financial (portfolio, insurance, etc.) analytics.