Authors
Matthew Flynn, PhD, Director and Head of Machine Learning, Aetna
Mary Loveless, JMP Systems Engineer, SAS
Bike-sharing programs in New York City provide New Yorkers and visitors alike with a transportation option for getting around the city. Bike renters need to know whether a bike is available at a desired starting location station and whether there is docking space to drop off the bike at a specific destination station. Bike availability information, supply, demand and rebalancing of the bike stations are critical to ensure a positive customer experience. We use JMP scripting and SAS to automate the process of retrieving publically available data at multiple time intervals. We transform the data in SAS and pass it to JMP to generate interactive visualization and analysis reports. Street-level mapping, Graph Builder, bubble plot, data filter, time series and other analyses will be showcased in a live demo. This presentation will show that interactive visualization and street-level mapping are effective methods to look at rental availability, pick-up and drop-off locations. In addition, they are strong methods of communicating information to management about business and marketing development programs.
