I’m doing some form of data visualization learning for 180 days because I need to #JFDI.
Reading and Learning Data Visualization Theoretically/Critically:
I went to Visualization and the City: A Talk with Claudio Silva, a professor at NYU working with visualizing NYC City Data, projects such as TaxiVis
Three Takeaways from talk:
- Biggest difficultly is not scaling with computing power, but with people and processes – eg personnel, how to connect data scientists with domain experts
- Auto anomaly detection methods important with working with big data
- Think about making tools and visuals that “operate with speed of brain” in terms of load time, interface, etc.