INTERNATIONAL MASTER IN BUSINESS ANALYTICS AND BIG DATA

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1 POLITECNICO DI MILANO GRADUATE SCHOOL OF BUSINESS BABD INTERNATIONAL MASTER IN BUSINESS ANALYTICS AND BIG DATA Courses Description A JOINT PROGRAM WITH POLITECNICO DI MILANO SCHOOL OF MANAGEMENT

2 PRE-COURSES STREAM 1: MANAGEMENT BASICS Strategy and Marketing This course illustrates the economic value as a driver of strategic actions. It focuses on business model and strategic positioning choices, competition analysis and dynamics of interactions in the supply chain, competitive advantage (business portfolio strategy, vertical integration, costs and attractiveness advantages). It presents the business plan and industrial plan as summary tools supporting corporate strategy. Furthermore, it describes the marketing decision making process: demand analysis, segmentation and targeting, value proposition and positioning, marketing mix (Product, Price, Promotion and Place). Accounting and Finance This course introduces participants to the balance sheet analysis and the difference between economic and financial variables. It also illustrates accounting principles, industrial accounting and management control, investment valuation principles. Organization Design This course describes the principal variables in organizational system design and illustrates the design of roles and jobs and the organizational structures. It also focuses on process management and modeling and on human resources management systems. Supply Chain Management This course introduces participants to Supply Chain Management (SCM), its evolution over time and its strategic role. It also describes SCM performance (costs and service level) and strategies (Lean, Responsive, Risk-Hedging, Agile), illustrates source and purchasing process and organization and deals with production planning and control. 2

3 PRE-COURSES STREAM 2: IT BASICS Software Engineering This course is aimed at analyzing the evolution of software development both from technological and methodological perspectives. It focuses on software process, lifecycle and development models. Other topics addressed are software quality, relational development systems, UNL/requirement analysis and lifecycle management. Data Management This course is aimed at describing tools for collecting and analyzing data and finding information. An introduction to probability is also provided. Information Systems Architecture This course introduces participants to information systems. It describes their different types and Anthony s pyramid. It presents On Line Transaction Processing (OLTP) and On-Line Analytical Processing (OLAP). It also focuses on integration architectures, Enterprise resource planning (ERP) and Customer relationship management (CRM) systems: principal components, software selection, process modelling, BPMN, analysis of process quality and adaptive processes. 3

4 DATA MANAGEMENT AND WAREHOUSING Business Models This course illustrates the relations between IT and organizational models and shows how IT-business alignment is a driver for data availability. It presents a taxonomy of business data sources and deals with data availability, data quality and data analytics, showing also the impact of data analytics on business. Moreover, it focuses on data analytics outsourcing in terms of market services and business models. Data Management - Data Integration This course describes data management in information systems at the time of big data and shows how to organize unstructured, heterogeneous and inconsistent data integration. Enabling Infrastructure The aim of this course is to provide the basic concepts of information systems: hardware, virtualization, networking, storage and data center. Big Data Cloud Technologies This course illustrates the architectural components of big data infrastructures. It focuses on hardware infrastructures (sizing and scaling), Hadoop Stack and design principles and shows how to implement and manage big data systems. Semantic Web and other data processing technologies Variety is one of the most critical big data dimensions and still represents an open challenge. This course is aimed at illustrating standards and tools for variety management. It presents the RDF data model, the ontology language to define OWL dictionaries, the SPARQL Protocol and RDF Query Language, the mapping language R2RML, and shows how to use them for managing data integration through the Ontology Based Data Access. Other topics addressed are serious games, data security, encryption and data masking, data erasure, backups, international laws and standards. 4

5 FUNDAMENTALS OF STATISTICS AND DATA VISUALIZATION Fundamentals of Statistics This course is aimed at describing univariate and multivariate exploratory data analysis through graphical analysis of numerical and categorical attributes, quantitative measures (central tendency, dispersion, relative location) for numerical variables, measures of heterogeneity for categorical variables, measures of correlation. It also deals with feature extraction methods for dimensionality reduction, such as Principal component analysis (PCA), Independent component analysis (ICA), Multidimensional scaling. The course focuses also on Object Oriented Data Analysis and provides realworld cases. Data Visualization This course presents the different forms of data visualization referring also to the data visualization process and the involved roles. It describes the impact of data visualization at corporate and IT levels and illustrates the basic principles of visual communication and synthetic graphical representation. It focuses on the delivery of data and on the good and bad practices (critical analysis and concrete examples) and provides an overview of the main tools for data discovery and exploration. 5

6 PREDICTIVE ANALYTICS AND BUSINESS APPLICATIONS Big Data opportunities and applications This course describes opportunities and critical factors in big data applications through use cases. Furthermore, it deals with scalability issues and constraints of modern storage and computing platforms. Big data opportunities for distinct objectives and business problems are also presented. The course finally illustrates big data ecosystem and its relation with business intelligence tools. Predictive analytics and machine learning This course is aimed at describing the most prominent machine learning methods. It illustrates simple and multiple linear regression. It provides a taxonomy of classification models and presents several classification techniques, such as classification trees, Bayesian methods, logistic regression, neural networks and support vector machines. It describes clustering methods (partitioning-based and hierarchical algorithms) and association rules. The course also presents feature extraction techniques for nonlinear dimensionality reduction. Business applications of advanced analytics The purpose of this course is to provide real-world examples of predictive analytics in different application domains and industries. Lectures are supplemented by active class discussion, computer-lab activities and use of software tools. PROJECT & PEOPLE MANAGEMENT Project Management This course is aimed at illustrating principles and methods of project management. Change Management This course presents the different approaches to change management, the critical aspects, the management tools, the communication. Radical and incremental changes are also described. Soft skills This course illustrates individual behavior and in-team behavior in terms of team working and leadership. Public speaking is also addressed. 6

7 ANALYTICS FOR MANAGEMENT More than technology: personal skills This course is aimed at describing the set of management, leadership and communication skills required to maximize the impact of business intelligence and predictive analytics on business and organization. Supply Chain Analytics This course presents advanced analytics for supply chain management dealing with the design and optimal sizing of logistic networks, supply and distribution and operations management. Finance Analytics This course illustrates the application of advanced analytics to finance, with a specific focus on risk management, credit scoring, high frequency trading and portfolio optimization. Marketing Analytics This course describes the use of advanced analytics for marketing applications, such as customer targeting for retention and cross-selling campaigns, social media analysis, pricing optimization and market based analysis. Organization/HR Analytics This course illustrates advanced analytics applied to organization and HR management for organizational design based on social network analysis, performance and retention analysis, staff sizing and career pathing. 7

8 VIA LAMBRUSCHINI 4C, BUILDING 26/A, MILANO - ITALY TEL FAX

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