Universidade Santiago de Compostela
Master's Degree in Mass Data Analysis Technologies: Big Data
Santiago de Compostela, Spain
DURATION
1 Years
LANGUAGES
Spanish, Galician
PACE
Full time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Oct 2024
TUITION FEES
EUR 1,089
STUDY FORMAT
On-Campus
Introduction
The purpose of the Master is to provide training in advanced scientific, technological and socioeconomic aspects related to an essential challenge of Information Technology today: the huge amount of data generated and the need to manage it effectively and efficiently to produce value-added services.
In the 2015/2016 academic year, the Interuniversity Master's Degree in Massive Data Analysis Technologies: Big Data begins. The master's degree was positively evaluated by the National Evaluation Agency and on 4/30/2015 it was declared an official degree by the Council of Universities.
It is one of the first Masters verified at a national level (and declared official by the Council of Universities) on the subject of Big Data.
The purpose of the Master is to provide training in advanced scientific, technological and socioeconomic aspects related to an essential challenge of Information Technology today: the huge amount of data generated and the need to manage it effectively and efficiently to produce value-added services. Specifically, the master focuses on the processing, storage and access to massive amounts of data to explore and analyze them, extracting knowledge and making requests.
Curriculum
It consists of a single academic year (60 ECTS) with three large training blocks: Big Data, Data Science and Business Applications.
The study plan consists of 9 subjects and a Master's Thesis (TFM). Elective subjects or internships in companies are not contemplated. This gives rise to an academic offer of 60 ECTS (18 ECTS from the TFM and 42 ECTS from other compulsory subjects).
Teaching is taught jointly by the University of Santiago de Compostela (USC) and the University of Murcia (UMU). Specifically, the degree is coordinated by the Higher Technical School of Engineering (ETSE) of the USC. The Master will be taught in the afternoon.
Program Outcome
It is a primary objective of the program to develop the skills and competencies necessary to process, store and access massive amounts of data (in a variety of formats and using efficient large-scale computing strategies), to explore and analyze that data, extracting knowledge from them and making predictions, and to identify new business areas and value-added services that, assisted by this type of intelligent decision support technologies, can give rise to innovative and competitive products or services for companies or institutions public.
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Career Opportunities
Currently, there is a great demand for professionals with skills in this area. Depending on the intensity of their specialization in the three fundamental areas (Computing, Prediction or Business) we find different types of new professionals and scientists.
Big Data Programmers (or “Data Developers”), Data Analysts or Scientists (“Data Analyzers” or “Data Scientists”), and data expert business professionals (“Data Businessman”) are some of the new professions that have emerged around the world. Big Data.
This new study plan covers these major areas transversally so that graduates would be in the best position for their future activity, both at a professional level in companies from various sectors and at a researcher level in private R&D&I centers or teams. or public, and/or for the completion of a doctoral thesis in any of the areas indicated above.
The Master's Degree therefore involves postgraduate training specialized in advanced scientific, technological and socio-economic aspects related to various branches of knowledge, including several sub-areas of Computer Science and Mathematics.
The aim is to prepare versatile graduates who can develop their activity in the development and application of Big Data Management and Analysis technologies in a broad sense, with the possibility of easy adaptation to different work environments and different future specialization profiles after completing the Master's degree. (Big Data computing professionals, data scientists or analysts, researchers in Data Mining or Distributed Computing, etc.).