Efficient and effective processing of such data for actionable knowledge might result in better performance of the organization by exploring mainly data analysis techniques. These include various statistical and data mining (data exploration) techniques, specifically targeted for the extraction of actionable knowledge from large volumes of existing data.
All that knowledge serves, ultimately, to support decision making. According to a recent report by the McKinsey Global Institute, data mining will drive the next wave of innovation.
The Scientific Board of the programme can be consulted here.
The Master course is destined to (potential) decision-makers wishing to add value to their strategic capabilities by taking advantage of information decision support and data analysis techniques, as well as specialists in information processing wishing to participate in the development of computational systems for business intelligence and decision support. Our current and past students:
The Master in Data Analytics is designed for those who wish to promote their professional development, as well as those who need a basic scientific and technical training to update their knowledge about the latest advances in the respective areas. The sectors where the knowledge and technique can be applied are diverse. They include distribution, banking, manufacturing, insurance, transport, industry, retail, services (including health) etc.
"Medidas de Grafos Bipartidos em Empresas Cotadas em Bolsa"; Ana Lúcia Pinto Neto Veloso; Supervisor: Pedro Campos
"Analysis of OECD Countries Well-being through Statis Methodology"; Fabricio Zambrano; Supervisor: Adelaide Figueiredo
"Modelo de Apoio à Decisão Multicrédito para a Avalição de Desempenho de Motoristas numa Empresa Portuguesa de Transportes Rodoviário"; Raquel Morte; Supervisor: Maria Pereira
"Failure Prediciton - An Application in the Railway Industry"; Pedro Pereira; Supervisor: João Gama
"Dinâmicas de Comunidades em Redes Sociais de Grandes Dimensões"; Vitor Cerqueira; Supervisor: João Gama
"Selection of a Strategic Plan Using Multi-objective Optimization"; Evgeniya Shamonova; Supervisor: Dalila Fontes.
Students doing this master can apply to the QTEM Network Master. It will allow the student to take the master at FEP and at the same time take a specialization in Quantitative Techniques for Economics and Management. Students doing QTEM can spend 2 semesters abroad in the prestigious member universities of the network. They must also do an internship. More informations here
The master in Data Analytics is in the 17 th place in the Eduniversal Best Masters Ranking 2016-2017 of the best programs of Information Systems Management in Western Europe.
The course list of the Master programme can be found here.
The master’s programme comprises: a) an organized set of subjects that account for 75 ECTS credits. This part of the programme leads to the grant of a master’s programme diploma in Data Analytics, but not to an academic degree. b) A dissertation, or an original work written specifically for the master’s programme, or a professional traineeship (in Portugal or abroad) combined with a final report, which accounts for 45 of the total 120 ECTS credits granted by the programme. The public oral presentation of this dissertation or report in viva voce can lead to the award of a Master’s degree in Data Analytics.
Students enrolled / admitted in 2017/18
26 February to 30 March 2018 (1st call)
Prior reading of the Official Notice is mandatory.
More information on access conditions and criterias, among others, here.
Information about tuition fees here.
"I decided to apply to this Master with the personal and professional goal of improving skills and learning new subject areas in the data mining field.I have acquired a valuable knowledge which allowed me to grow professionally. With the implementation of intelligent systems my company is providing a better service and experience to our customers. I believe this Master is a great investment to everyone who wants to learn how to implement forms of advanced analytics, such as data mining, predictive analytics or text mining to gain a competitive edge.” Cristina Cerqueira, Farfetch."
"I took the Master in Data analytics in order to learn cutting edge data analysis methodologies for the resolution of complex problems in order to create actionable knowledge that is a source of competitive advantage. The experience gained during my master programme contributed to my professional development, in which segmentation, propensity and network analysis became part of my vocabulary in my work in Customer Intelligence." Nuno Paiva Business Intelligence Manager NOS."