Checking date: 19/05/2022

Course: 2022/2023

Data Design for sensemaking
Study: Bachelor in Data Science and Engineering (350)

Coordinating teacher: DIAZ PEREZ, MARIA PALOMA

Department assigned to the subject: Computer Science and Engineering Department

Type: Electives
ECTS Credits: 6.0 ECTS


Skills and learning outcomes
Description of contents: programme
1. Context of Data Governance 2. Data integration models (datawarehouse and virtual models) 3. Heterogeneous Data. Mediated Schema. Schema Matching and Mapping. 4. Obtaining Data. Crawlers. Wrappers. Data Integration on the web. 5. NoSQL databases in data integration. 6. Sensemaking and Situational Awareness in the Big Data Era 7. Visual Analytics: History, Definition and Building Process 8. Principles of Human Computer Interaction: Perception, Cognitive Aspects, Semiotics and Creativity 9. Interaction with Visual Interfaces 10. Geo-spatial and Temporal Data Processing 11. Deep Learning Models 12. Applications of Visual Analytics
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

The course syllabus may change due academic events or other reasons.