48 hours long Data Analytics Hackathon during which we were asked to analyze several datasets from the city of Lugano to exploit useful information. My team managed to inspect and interactively visualize on a map the bike-sharing usage, in order to understand how the owner company could improve service availability through bikes-relocation during the day. A further integration with data from other sources, regarding commuters and public transports, has been used to drive some conclusions about available marketing choices for bike-sharing spreading over the Lugano community.
Tools: Elasticsearch & Kibana (exploratory data analysis), Knime Analytics Platform (data manipulation), R Shiny (interactive visualization on a map through Leaflet)
- Paolo Montemurro
- Marco Ferri
- Riccardo Giordano
- Hao Ma
- Giovanni Kraushaar
- Simone Caggese
- PubliBike
- TPL
- SwissCome