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Knowledge and understanding: "The student acquires programming knowledge especially directed towards data analysis and statistical methodologies aimed at the implementation of models as well as the analysis of large datasets. In particular, computer skills are oriented towards machine learning methods, knowledge of modern data management and storage techniques, also from heterogeneous sources in terms of type and structure, including spatio-temporal data and high-dimensional data also in a cloud environment, and the implementation of algorithms for massive data. This knowledge is then complemented by the indispensable knowledge of textual data and network analysis and aspects related to the security and privacy of such data." The student acquires specific knowledge of the economic and business domains of his or her interest and necessary to address decision-making and management issues in public and private organisations with an interdisciplinary perspective. In the Data Analytics for Economics track, knowledge will be oriented towards economic theory, economic analysis and econometrics through the development of micro- and macroeconomics, decision theory under conditions of uncertainty, time series analysis and forecasting techniques, and methods for causal inference from both administrative and experimental data. Knowledge will also be oriented towards data analysis. In the Business Analytics track, the knowledge acquired will concern the tools necessary for analysing and interpreting business and organisational data, as well as business economic measurements, business models and their evolution, tools and techniques to support decision-making, performance measurement systems consistent with digitisation and sustainability processes, the governance of marketing processes, with particular regard to digital and interactive marketing and the impact of digitisation on marketing activities. Aapplying knowledge and understanding: Ability to apply and implement, through the development of algorithms, techniques for the analysis of large datasets and for spatial and temporal data, under conditions of uncertainty, in order to ensure the usefulness, quality and effectiveness of the analysis. Capacity to use IT technologies, techniques and methodologies for acquiring, managing, integrating, analysing and visualising large datasets, in order to ensure scalability with respect to the volume and speed of data acquisition. These skills relate in particular to database management systems and large datasets and their visualisation techniques, models and languages for expressing data semantics, learning techniques, decision-making models, organisation of information systems, web search techniques, data flow management techniques. Ability to analyse business problems that characterise data-driven decision support through the application of statistical and computational models. Ability to use and apply models for market analysis and economic policy formulation. Making judgements: Master's graduates will have the ability to apply the acquired knowledge to interpret data in order to make directional and operational decisions in an economic-business context. Master graduates will have the ability to apply the acquired knowledge to support processes related to production, management and risk promotion activities and investment choices through the organisation, analysis and interpretation of complex databases. Communication skills: Master's graduates will be able to communicate effectively in oral and written form the specialised contents of the individual disciplines, using different registers, depending on the recipients and the communicative and didactic purposes, and to evaluate the formative effects of their communication. Learning skills: "MSc graduates should be familiar with the tools of scientific research. They will also be able to make autonomous use of information technologies to carry out bibliographic research and investigations both for their own training and for further education. In addition, through the curricular teaching and the activities related to the preparation of the final thesis, they will be able to acquire the ability - to identify thematic links and to establish relationships between methods of analysis and application contexts; - to frame a new problem in a systematic manner and to implement appropriate analysis solutions; - to formulate general statistical-econometric models from the phenomena studied.