In March, IBM held an analytics event with the Center for Technology Management at Columbia University. This event was the first session of a two-part data science challenge focused on analyzing city dynamics to uncover sustainable and incremental business opportunities for commercial and public entities. The session covered both theoretical and practical aspects of the spatio-temporal analytics techniques through select client uses cases. In addition, there was an interactive session in groups with IBM practitioners that enabled students to brainstorm and ideate further on how to leverage hyper-local geo-temporal data to solve a client problem.
Students were divided into teams and utilized sample data from IBM’s Metro Pulse Powered by Watson offering, which combines a diverse set of time-sensitive, hyper-local city data with cognitive computing. Each team had an IBM appointment mentor, and worked together to solve consumer business problems.
On April 28th, the students were invited to a follow-up session in which the top two teams presented their findings. The top two finalist teams received recognition for their efforts, with a team of Applied Analytics master’s students - Zeren Bai, Kejuan Jiang, Ling Qi, and Zhan Zhang - named as the top submission.
