The economic and business panorama is characterized by the dissemination of large masses of data, subject to rapid processes of obsolescence and change. Thus, there is a strong demand by institutions and companies for profiles capable of managing the data flows in the environment, analyzing them and creating models that reduce uncertainty based on the evidence provided by the data. The Master's Degree in Economic Data Modeling and Analysis trains professionals capable of applying management techniques and analysis of masses of data to extract relevant information, and of applying the appropriate quantitative models to make decisions.Training objectivesThe main training objectives of the Master's Degree in Economic Data Modeling and Analysis are:Provide students with a professional profile specialized in the management and analysis of economic data, and in the construction of quantitative models to support decision-making, in accordance with the current demands of companies and institutions.
Train students in the use of software and programming languages specifically designed for data analysis and the construction of quantitative models of economic analysis, especially in the case of free-use software.
Provide adequate data analysis and modeling tools for analysis in various specific branches of the Economy of particular relevance.
Provide quantitative analysis tools oriented to the economic field that contribute to the exercise of research activity.
Provide a broad and realistic vision of the world of Big Data, with special impact on the economic planeCompetenciesKnowing how to work in multidisciplinary teams, obtaining relevant results in the economic and business field.
Being able to develop innovative and competitive proposals in research and professional activity in the economic field.
Being able to identify problems and evaluate the applicability of the most appropriate analysis and modeling techniques for their resolution.
Being able to present the results of an investigation or a report, by technological and digital means, in any specialized medium or before any professional forum.
Be able to carry out autonomous and responsible learning.
Know the main advanced database architectures and the environments for their consultation, management and use.
Being able to obtain data from various economic-business sources and prepare them for processing.
Being able to analyze the structure of an economic sector using multivariate statistical techniques, using specialized software.
Know the concepts and tools for data management associated with Big Data, and be able to apply models based on this technology to the economic sphere.
Be able to apply advanced analysis and modeling techniques based on statistical learning to business-economic data using specialized software.
Being able to apply capital, profitability, and risk asset valuation techniques in financial markets, using specialized software.
Being able to generate advanced prediction systems in the economic-business environment, using specialized software.
Being able to estimate econometric models for the representation of complex economic-business systems, using specialized software.
Being able to analyze the territorial dimension of socioeconomic systems, and to estimate spatial econometric models, using specialized software.
Be able to estimate panel data econometric and microeconometric models in various areas of the economy, using specialized software.
Being able to integrate different data analysis and modeling methodologies in the face of a complex economic-business problem.Professional outingsData experts company professionals (businesspeople): leaders, managers, entrepreneurs; but with a solid technical background in information analysis.
Data analysis creatives: experts in the management and exploitation of a wide variety of data sources of an economic nature, and in the use of analysis tools.
Programmers (data-developers): focused on programming code for analysis, statistical treatment and machine learning developments, often in companies and production environments.
Data analysts (data-researchers): people with a scientific and research career who apply their knowledge to the organization of data flows, especially in the economic field.
Data Scientists: professionals capable of extracting and interpreting, based on the business in question, the relevant information contained in the vast amounts of data generated by the company's own activity and its relationships with third parties (customers, market, etc.). They design, develop and implement complex mathematical algorithms based on statistical programming, machine learning and other methodologies.
These studies also come from specialized training in the analysis and modeling of data of an economic nature in order to undertake doctoral studies, and a research career in general, especially in the branches of Economics and Business Administration.Regarding sectors in which the profile of the graduate can arouse special interest, the following stand out, among others: companies based on the digital economy; small, medium and large companies, banking and finance; consulting companies; research institutes and study services. These studies also provide the graduate with very useful skills in the field of entrepreneurship and the creation of start-ups and, in general, in the field of dynamic sectors with a high degree of innovation.Admission profileThe recommended entry profile for people who are going to start the studies of the University Master's Degree in Modeling and Analysis of Economic Data is that of motivated people with initiative, with a high interest in acquiring advanced and specialized training on management techniques, analysis and modeling of data of an economic nature; training that is widely demanded by different economic and business institutions, in order to understand the reality that surrounds them and thus be able to make quick and timely decisions.
Therefore, these people are required to want to develop a professional or research career in the field of data management, analysis and modeling, and quantitative economics in general.
Given the orientation and objectives of this Master, it is especially suitable for students from a bachelor's degree in Business Administration and Management, or related degrees such as a bachelor's or bachelor's degree in Economics, Accounting and Finance, etc. However, as indicated in the section relating to the justification of the degree, the Master in Modeling and Analysis of Economic Data may be of interest to senior engineers and Engineering graduates who wish to deepen their knowledge of Economics and Company as in the acquisition of skills for the management, analysis and modeling of masses of data in general, and of an economic nature in particular.
On the other hand, although no special access tests are established, students interested in this program must have a sufficient command of the English language to be able to understand scientific texts, be able to write documents and reviews, and communicate with certain fluency. Therefore, to be admitted to this Master, the student must prove that they have a B1 level of English in accordance with the criteria established by the University of Castilla-La Mancha in the Governing Council of March 2, 2010. In that case The supporting document will have to be presented by the student together with the admission application. The Academic Committee of the Master reserves the right to use other procedures if necessary.Admission criteriaThe Academic Committee of the Master will take into account the following criteria, granting them an assessment on a scale of 0 to 10 points:Academic record of the applicant in the degree for which he requests access to the Master (65% of the final assessment).
Possession of other degrees different from that of the previous point, in the branches of knowledge of Economics and Social Sciences, and Engineering (15%).
Complementary training in the field of data analysis (10%).
Previous experience in the field of statistical / econometric data analysis using specialized documentary-accredited software: work experience, reporting, publications (5% of the final assessment).
Knowledge of the English language (higher than level B1) (5%).