Access the most in-demand knowledge at present with a program fully compatible with professional activity.
SANFI and the Foundation for Financial Innovation and the Digital Economy join forces to offer a program that meets the urgent need for professional trained in the field of big Data, and able to apply this to a range of Economic areas.
Train people in different areas of the digital economy so they can understand the fundamental knowledge and implications of the important changes new technologies are provoking in society, the economy and corporate business models. In particular, they will specialize in analysis and use of the data individuals generate in the context of the intelligent society. Scientific and commercial analysis of the huge amount of data present technology allows us to compile offers key commercial opportunities for companies and, in particular, for financial intermediaries.
Methodology is based on the development of eminently practical activities. The objective is to facilitate concrete tools, both operative and practical, through the exercises proposed.
This Master's is comprised of two methodologies:
- Classroom (150 hours): classes based on case studies in the development of activities.
- E-learning (350 Hours): Master develops a number of hours online allowing the students to manage their own learning, reducing the number of hours face-to-face and encouraging course compatibility with professional activity.
- Master’s Thesis (50 hours): development of a real application of Big Data analysis proposal for a business model or institutional activity.
Students enjoy access to individual tuition for any doubts which may arise during the course.
The program is taught by an excellent teaching team of executives and professional experts, together with highly experienced university professors.
The face-to-face classes are held in the Madrid SANFI center on Friday afternoons and Saturdays, once or twice a month until the program’s conclusion.
- The Digital Economy Concept.
- The Intelligent Society Concept.
- Technology Catalysts of the Socioeconomic model change.
- Artificial Intelligence.
- Cloud Computing.
- Internet of Things (IoT).
- Elements of Social Transformation: social networks, longevity, transhumanism.
- Personal data and data generated by objects.
- Data ownership.
- The consequences of third party knowledge of data.
- Bias provoked by data accumulation. Areas of discrimination.
- Control and ownership of identity.
- Regulatory systems.
- Models of regulatory sandboxes.
- Legaltech and Regaltech.
- Internet law.
- Legal aspects of cloud computing.
- Data protection regulation: personal data and data of things.
- Privacy regulation
- Digital identity and on-line reputation.
- The value of personal data and the right to forget.
- The present banking model: evolution, situation and transformation.
- Variables of the finance-banking context.
- The new technology based disintermediation model in the financial.
- Financial disruption and the appearance of Fintech.
- The role of Big Tech in the financial sector: the Techfin challenge.
- Digital banking models.
- Openbanking and the impact of financial regulation: PSD2 and MIFID II.
- Blockchain technology impact in the financial sector.
- ICOs as an alternative source of business.
- Big data.
- Concept, origin, basics and debates.
- Big data basics and analytic use.
- Scenes and examples of Big data use.
- Business Intelligence (BI).
- Introduction – Basic concepts.
- Business Intelligence Project Management.
- Control Instruments and KPSs (Key Performance Indicators).
- Big Data Business Intelligence Tools.
- Data Governance.
- Data sources.
- Origin and nature.
- Classification (by structure, form, and velocity of distribution).
- Verification of data quality.
- Analytic thought and corporate information systems: ERP, CRM, SCM.
- Open Data.
- Concepts and characteristics.
- Location and existing Open Data resources.
- Open Data applications.
- Data storage.
- Relational data bases (SQL).
- NoSQL databases.
- Data Warehouse and OLAP analysis.
- ETL Processes.
- Concepts of statistics and programming in R.
- Python and Big Data extensions.
- Data analysis with Artificial Intelligence.
- Machine Learning.
- Natural Language Processing (PLN).
- Big Data architectures.
- Hadoop ecosystem.
- Apache Pig.
- Apache Hive.
- Apache Spark.
- Cloud solutions and tools.
- Google and Microsoft big Data Tools.
- Data and results visualization.
- Big Data App developments phases for Business Intelligence.
- Business analysis: models and algorithms.
- Choice of architecture and tools.
- Data source selection.
- Process analysis.
- Economic/finance management.
- Marketing and sales.
- Operations and logistics.
- Human resources.
The University of Cantabria Master’s degree in Big Data and Digital Economy will be awarded on course completion.
Matriculation fees are 8000 €.
Admission requisites: holder of an officially recognized Spanish university degree (First degree or equivalent, Engineer or Architect, Diplomas or Technical Engineer) or previously homologated equivalent qualifications form other educational systems of similar level.
Course admission is possible without having obtained a University Degree, if the candidate can accredit a reduced number of pending credits for completion. According to the University of Cantabria rules experienced professionals may be admitted providing they meet University requirements.
Selection will be made following a rigorous process in which the curriculum and personal attributes of the candidate will be valued. Following the initial selection, a personal interview will be held with each of the selected candidates.
The admission process is OPEN and the NECESSARY DOCUMENTS are:
- Application form (download here)
- Curriculum Vitae.
Documents should be sent by email to email@example.com.