This course aims at presenting the tools and methods located at the ends of the Big Data processing chain: visually exploring data before modeling them, visually communicating analysis results. This step is crucial for data analysts, but also for decision makers who need to understand complex results without being experts, through intuitive graphical interfaces and dashboards.
- Introduction to data visualization;
- Principles of visual encoding, perception, cognitive principles and design;
- Typology of graphics, interaction and animation techniques;
- Case studies, paper prototyping;
- Algorithmic aspects and software architectures of visualization;
- Case studies and use of industry standard tools (Tableau, Raw, Google Fusion Table);
- Web visualization project.
Written exam and web project (+ defense)