Story and Inspiration:

This particular challenge provided an opportunity to use the IBM Big Insights in the cloud. The main motivation was to gain hands-on on the IBM world of Hadoop products by participating in this challenge. However, I must say while evaluating Big Insight, I realized how a visualization would have a substantial impact in the way insights are perceived. Initially I was just not sure what all I could do with the dataset. However the visualization helped me to figure out more and more use cases that I can apply to the data. This in a way took me to next level to find different ways to analyze the data. The impact the services like CitiBike could have on Metro cities is tremendous and that is precisely the reason to choose this dataset. Moreover, I could visualize some initial use cases around the data when I started.

Target User:

Anyone who would be interested to know some interesting statistics about CitiBike yearly data.

Key Features:

  • Gender Distribution amongst the Bikers
  • Impact of Weather on the Trips or Rides
  • Busiest stations throughtout the year
  • Top Destinations where Bikers ride from Busiest stations
    • Self-made Custom Bicycle Icon representing Station on the map
  • Number of rides based on the Duration of ride

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