Máster Universitario en Análisis y Visualización de Datos Masivos / Visual Analytics & Big Data

Specialize with the most complete study plan with the online Master in Big Data

Prepare to achieve a versatile profile capable of adding value in different sectors and companies. The online Master's in Big Data program has a multidisciplinary approach and includes specific engineering subjects such as massive data processing, visualization tools or data analysis and interpretation. In addition, you can do your Master's Thesis (TFM) on real cases of the company in which you are already working.

Consulta la distribución de asignaturas por cuatrimestres y sus contenidos, las competencias a adquirir, la metodología de aprendizaje, el proceso de evaluación, la bibliografía asociada y orientaciones para el estudio.

Primer Cuatrimestre

• Databases for Big Data
• Data Analysis and Interpretation
• Artificial Intelligence Techniques
• Engineering for Massive Data Processing
• Visualización Interactiva de la Información

Segundo Cuatrimestre

• Visualization Tools
• Data Governance and Decision Making
• Business practice
• Trabajo Fin de Máster

Prácticas Profesionales

Professional internships are mandatory and require a charge of 6 ECTS (126 hours). You have the option of doing them in person or online in companies with which we have agreements such as Telefónica, Banco Santander or Vodafone Spain. You can also do them in your own company if you currently work there.

These internships will give you experience and open job opportunities in the world of big data . Additionally, you can validate them if you meet the requirement for work hours in data analysis. You have the possibility of validating the internships of the Master in Big Data , if you wish, as long as you certify a minimum of 180 hours of work carried out in the field of data analysis. Some of the activities carried out may be:

• Development and/or deployment of global data monitoring, analysis and visualization systems to support decision making.
• Design of data capture and storage methodologies.
• Review of data catalogs and proposal of analysis techniques appropriate for a given context.
• Implementation of data analysis techniques
• Deployment of Big Data processing tools (Hadoop or similar)
• Design and/or implementation of interactive, usable and eloquent data visualizations
• Evaluation of existing capture and storage methods and preparation of improvement proposals.
• Evaluation of existing data analysis software and preparation of improvement proposals.
• Evaluation of existing data visualizations and preparation of improvement proposals. Design and develop a system to support decision making, contemplating the complete process: data collection, processing and visualization.

Perfil Profesional

At the end of the program you will be trained to:

• Identify the different phases required to create a good visualization, such as data collection, processing and representation.
• Diseñar un método de recogida de datos que consiga mapear en datos concretos una actividad, tarea o proceso.
• Use existing techniques and tools for data mining, statistics and information visualization.
• Develop interactive, usable and eloquent visualizations.
• Create and develop a system to support decision making, contemplating the complete process: data collection, processing and visualization.

To enroll in UNIR 's official Master's Degree in Big Data, in addition to the legal requirements, we recommend that you be interested in:

• The management, extraction and analysis of big data.
• Get relevant information in big data.
• Improve company processes.

The possibilities of big data are endless. Companies and organizations require trained and versatile professionals who know how to analyze and extract value from big data in different sectors and work environments. Become a specialist and work in positions such as:

• Data engineering , responsible for extracting and preparing data so that it can be processed. To do this, you must determine the technology and infrastructure required, both on a small and large scale, so that the extraction of information is done efficiently and achieving high scalability.
• Chief data officer (CDO) - you will be the person in charge of data in a company. This is a profile associated with management whose functions include defining security policies for data storage, ensuring compliance with the law, coordination between the affected departments, promoting data-based decision-making, etc.
• Data architecture (data architect) , you will be responsible for designing and 'building' the infrastructures that support big data, ensuring their proper functioning and security.
• Data scientist , in addition to data extraction and visualization, you will be responsible for analyzing and adding value to data, adapting to the particularities of each organization.