Programming, Algorithms and data structures, Files and databases

1. Data integration models: data store based models and virtual models 2. Data acquisition: Crawlers. Web data integration 3. NoSQL databases in data integration 4. Situation awareness and interpretation in the Big Data era 5. Visual analytics: history, definition and development process. 6. Principles of Human-Machine Interaction: Perception, cognitive aspects, semiotics and creativity 7. Interaction with visual interfaces 8. Temporal and geo-spatial data processing 10. Applications of visual analytics

* Lectures: 2 ECTS. They aim to achieve the specific cognitive competencies of the subject and the transversal competencies of analysis and abstraction. * Practical classes: 1,5 ECTS. They aim to develop the specific instrumental competencies and the transversal competencies problem solving and application of knowledge. * Case study: 2 ECTS. Started during the practical classes and completed outside of them, it aims to complete and integrate the development of all specific and transversal competencies with the design and implementation of a case study through group work. * Tutorials: TUTORIALS. Individual or group tutoring sessions organized by the teacher for the students. * Final exam: 0,5 ECTS. It aims to influence and complement the development of specific cognitive and procedural skills. It reflects especially the use of the lectures.