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MIRI - Data Science



The master’s degree equips graduates with solid knowledge and hands-on experience in techniques for managing, analyzing and extracting hidden knowledge from structured and unstructured big data ensembles and in building adaptive analytic systems that are able to exploit that knowledge in modern organizations. In particular, the master’s degree addresses the new challenges of the smart society boom: fraud detection, bioinformatics, information extraction from linked open data, real time analysis of sensor data and social networks, and customer relationship management.


The specialization in Data Science is aimed at students from all over the world. Candidates must have a bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related fields, as well as a good level of English, and they must be motivated to discover knowledge from data in the fascinating world of sciences and technologies. 




Four semesters. (120 ECTS)



Full-time: 20h lectures, 20h personal work per week
Part-time: half of full-time
Lectures are in the morning (8h-14h) 


¿Por qué este máster universitario?

Data contains knowledge

The primary social and economic value of modern societies is knowledge. For this reason, a mastery of information technologies for structured or unstructured information recorded in data warehouses, websites and social networks is indispensable for the development of individuals and the society in which they live.

This is even truer with the new paradigm of big data, as data are being generated by everything around us at all times. Every digital process and social media exchange produces them. Systems, sensors and mobile devices transmit them. Big data arrive from multiple sources at an alarming rate, in huge volumes and an extraordinary variety. To extract meaningful value from big data, you need optimal processing power and smart analytic capabilities. This leads to a new paradigm, “data value”. Data are the new driving force of businesses and governments, generating new scientific discoveries, creating new business models, providing better services, giving competitive advantages and improving decision making.

However, most of the data gathered are just noise (random fluctuation) and only a small part contains the signals needed to solve society’s present problems. Training highly specialized professionals in Data Science has thus become a crucial factor for improving the competitiveness and welfare of a country.

The skills needed to fully harness the power of big data analytics are data mining skills and business intelligence. Data mining skills encompass all of the methodologies for extracting information from data and expressing the amount of uncertainty in the decisions that we make. Business intelligence includes all of the technologies for managing large amounts of structured and unstructured data and helps to identify, develop and create new strategic business opportunities.

Oportunidades laborales

Data science has emerged as a significant field at the crossroads between science and technology. Data scientists help businesses, government, and society to leverage oceans of available data using very powerful and relatively cost-effective analytic technology. The ability to achieve the full potential of data analytics requires not just data, tools, and infrastructure, but also quantitative skills to traverse the huge mountains of data.

Graduates of this specialization may find employment in a range of sectors:


Using big data reduces fraud and errors and boosts the collection of tax revenues.


The prediction of classical epidemiological models can be greatly improved using genomic data.


Using big data analytic techniques drives efficiency and quality. In the developed economies of Europe, government administrators could save more than 100 billion euros in operational efficiency improvements alone, using big data analytics (McKinsey Global Institute, 2011).

Transparency in smart cities

By simply making data and analytics more easily available to relevant stakeholders in a timely manner, huge added value could be created.

Personal Services

Using data mining techniques for services enabled by personal-location data could capture 600 billion euros in consumer surplus (McKinsey Global Institute, 2011).


Big data analytics will become a key basis for competition and growth of individual firms and allow new products and services to be offered.

Individual entrepreneurship

Leading companies are using data collection and analysis to conduct controlled experiments that lead to better management decisions; others are using data for real-time forecasting to adjust their business levers just in time. Big data analysis allows narrower segmentation of customers and therefore much more precisely tailored products and services. Sophisticated analytics can substantially improve decision making. Big data analytics fosters the development of the next generation of products and services, i.e., manufacturers can use data obtained from sensors embedded in products to create innovative after-sales services such as proactive maintenance. It is obvious that the efficient usage of data mining techniques will substantially increase gains across sectors from computer and electronic products and information to finance and insurance.  

All of the internationally recognized journals and consulting institutions affirm the paramount importance of data mining, business intelligence, big data analytics and data science in their reports for the 21st century:

The market for BI platforms will remain one of the fastest growing software markets.


The market size grew to 14 billion US dollars in 2014, compared to 8.8 billion US dollars in 2008

The analyst firm Forrester

The field of data management and analysis is estimated to be worth more than 100 billion US dollars and grows by nearly 10% per year.

The Economist

The shortage of professionals in such fields is deemed to be 4.4 million in US for 2015



The McKinsey Global Institute, in its May 2011 report, states big data as the next frontier for innovation, competition, and productivity. In addition, it is worth mentioning that big data professionals have not been affected by the current economic crisis and are considered to be a top priority of CEOs everywhere.



Candidates must provide proof of their English proficiency, with at least a B2 level of the Common European Framework of Reference for Languages (or equivalent).

Required Documents

  1. Curriculum Vitae
  2. DNI, NIE or passport
  3. Academic Personal Certificate. The certificate must detail the number of hours and credits studied and must include the grade awarded for each subject. This certificate also must contain information on the mark scheme and how grades are awarded.
  4. Diploma (or similar document). This document must confirm that the duration of the degree was at least three years and that is it a valid precursor to studies at postgraduate level (master’s degree) in that country. If that is not possible, it must indicate the level of higher education that the degree gives access to in the country where it was awarded.
  5. English knowledge Certificate (minimum: B2 of Common European Framework of Reference for Languages)
  6. If the applicant holds other qualifications related to the subject area of the Master’s Degree course applied for and that are different from those given to meet entrance requirements, it is necessary to include the original certificates and copy (or official copy) with the application.
IMPORTANT: All documents issued in countries that do not belong to the European Higher Education Area must be stamped and legalised by the appropriate government department, and translated into Spanish or Catalan language.

The Academic Committee is in charge of final decisions on students admission. It bases its decisions on following:
  • Final average grade for undergraduate degree that provides access to the master's degree
  • Suitability of the candidate's previous degree. Holders of bachelor's degrees in disciplines such as Informatics, Computer Science, Information Technology, Computer Engineering, etc. will be given preference
  • Ranking of the university issuing the previous degree, using the most common rankings (ARWU, QS World University, etc.)
  • Academic performance on the previous degree
  • Experience in innovation and research projects
  • Additional university degrees


Once you're inside the application form, you must choose the master Innovation and Research in Informatics. Once selected this master, you will be able to select the specialization Data Science.

You’ll need to complete and submit our online application form to apply for a master’s course. Click the button below to begin the application process.

To pre-enroll, you will need to register online.
For additional help, see the FAQs.

Doble Titulación

What's MIRI

MIRI stands for Master in Innovation and Research in Informatics. This label identifies those programmes with a special focus on research and innovation. Graduates become the most knowledgeable and skilled professionals in their respective area. These programmes are highly specialized and they provide a two year immersion in the corresponding field.

The six MIRI programmes are:

Testimonio de los estudiantes

Lo que realmente me gusta sobre el máste de Data Mining and Business Intelligence es que combina los estudios sobre el análisis de datos y la gestión de los datos con el objetivo de acercarse a los dos campos; una necesidad hoy en día en el mundo de los negocios es contratar a gente capaz de combinar lo mejor de los dos. El primer año ya me dieron una base muy fuerte para comenzar y el segundo me permitieron escoger en que campos me quería especializar. Mi opinión es que no es sencillo y que se tiene que trabajar fuerte, pero las cosas que aprendes a lo largo del camino realmente merecen la pena!

Victor Herrero - Degree in Informatics Engineering at FIB

La búsqueda de la especialización apropiada en el análisis de datos era muy difícil de encontrar. Ahora que estoy realizando mi tesis de máster, puedo decir que la minería de datos y el máster de Business Intelligence, del MIRI, eran una opción muy buena. Combina clases de teoría avanzada con programación. Más expresamente, la combinación de estadística y capacidades calculadoras aprendidas aquí serán muy difíciles de superar en el mercado. Con las técnicas adquiridas, en el tiempo que todo está medido y convertido en datos digitales, jo diría que estamos preparados para abordar cada problema en el análisis de datos que nos puedan plantear. Entonces tenemos todas las posibilidades, pero como no se regala nada en la economía, tenemos que estar preparados para trabajar muy fuerte.

Jaime Andres Merino - Technical Computer Systems Engineering at Universidad Politecnica de Madrid

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