Why a Master in Big Data and Management?
The Master in Big Data and Management program prepares students to work effectively with complex, large-scale, real-world data and to create business value from it.
It focuses on improving the understanding of customer patterns to increase business and improve profitability. Working in big data management requires a highly interdisciplinary set of competencies: a deep practical expertise in programming and computer science, a good working knowledge of advanced statistical techniques, a thorough understanding of the business world, and excellent communication skills. Finding this set of competencies in a single person is rare. They need to be developed with the right mix of classroom and field learning.
The curriculum of the Master in Big Data and Management is designed to prepare students to create analytical models and interpret them from a business-oriented perspective. It prepares young professionals to pursue a career as a data scientist or a business analyst. Today many companies, including large industries, consulting firms, and marketing specialists are currently on the hunt for these types of professionals.
The Master provides students with 60 ECTS credits. It teaches them how to harness large amounts of data, design analytical models and how to interpret them to optimize business processes.
Among the competences provided:
- Skills to collect, process, and extract value from large and diverse data sets
- Capacity to work with different computing tools in order to address complex problems
- Capability to understand, visualize, and communicate findings to the top management
- Ability to create data-driven solutions that boost profits, reduce costs, and improve efficiency
Learning methods and key courses
- Top managerial education
- Combination of lectures and labs
- Field project Econometrics
- Linear algebra/Multivariate calculus
- Machine Learning
- Programming: Hadoop/Spark, Python, R, SQL
The Master is targeted for students with a BA or MS in Economics, Statistics, Engineering or other scientific disciplines. Fluent English and strong motivation are required.
Scientific Director and Committee
Giuseppe F. Italiano, Full Professor, Computer Science LUISS Guido Carli University
Giuseppe Ragusa, Associate Professor of Economics, Department of Economics and Management, University of Pisa
Paolo Boccardelli, Dean LUISS Business School
Luca Pirolo, Head of Master Programmes, LUISS Business School
Massimiliano Calogero, Partner at KPMG Advisory S.p.A.
Walter Ruffinoni, CEO NTT DATA Italy
Paolo Spagnoletti, Associate Professor in Information Systems and Organization at LUISS Guido Carli University,
Flavio Venturini, Innovation Director ICONSULTING