The beginning of the XXI century is characterized by a rapid and massive production of data called Big Data, which has led to the emergence of “new” data centric sciences (data science, data journalism, network science, digital humanities, digital urbanism) and the definition of new expertise profiles for dealing with it (data scientist/engineer/curator). This has led to new requirements and challenges. In this new context, data visualization stands as a simple yet powerful and interdisciplinary tool for doing findings and/or confirming hypothesis in data centric sciences. This lecture will address different techniques for visualizing Big Data considering Big Data visualization as a complex and greedy task composed of several steps (data collection, cleansing, integration, analysis and visualization).
- Present and analyse data visualisation & analytics problems
- Design & explain data cleansing techniques
- Design solutions for managing huge data collections
- Use visualisation techniques to proof hypothesis and explore data