An early start
Day 2 of the Rotman MMA Datathon started bright and early with participants arriving at the School for breakfast before the problem was introduced by Professor Dmitry Krass, Academic Director, MMA, Ian Williams, Manager, Business Intelligence and Analytics Unit, Toronto Police Service (TPS), and Dena Krieger, Data Scientist at Geotab.
The challenge revolved around using data made available by the TPS and Geotab to better understand the causes of traffic incidents in Toronto, and to make proposals on how they could be reduced.
Working as a team is key to success
Once the challenge had been released and explained, teams broke off into their study rooms, where they would spend the next six hours working with the data, ultimately working towards a solution which they hopefully would be asked to present as one of the top five teams.
Teams used a variety of software tools and programs languages, such as Python, R, SQL and Excel. A number of teams used SAS, which opened up the chance for an additional prize. Mark Morreale, the National Lead for Canada’s Academic Program at SAS, would make an award to the team he felt made the best use of the platform during the competition.
Being computationally proficient is a requirement for entry to the Rotman MMA program. Many applicants know at least one programming language, and students in the program have the opportunity to develop their skills further with bootcamps to start the year, and at least one tool being used in every course throughout the program.
Advice from faculty experts
After lunch, faculty coaches visited each team to answer questions and offer guidance on preparing the solution. With the vast amount of data provided by the TPS, and the additional data available via Geotab, it could be easy to get lost with analysis that does not help towards solving the challenge. With the limited time available, it was important that the teams stayed on track in order to meet the approaching deadline.
Once all participants had submitted their solutions, they had about an hour to take a break and work on their speaking notes should they be called up to present as one of the top five teams.
During this time, our judging panel scrutinized each submission, looking at how they had used the data, what conclusions they had drawn, and whether the solution can be implemented.
Once a decision was reached, the participants gathered in Desautels Hall, eager to find out if they would be called up to present.
The finalists are announced
The judges commented on how well all the teams had done within such a short space of time. However, the overall winner would come from one of the following teams:
- Team G
- Team H
- No Man’s Land
Called up in random order, each team had approximately 5 minutes to present, and then answering questions from the judging panel.
Once the presentations were over, our judging panel gathered once more to decide on the overall winner.
And the winner is…
Congratulations to Team G, pictured above, receiving a certificate to commemorate their win. Each participant from the team is eligible for a $5,000 CAD entrance award for the MMA program should they be apply and be successfully admitted to start in August 2019.
Durugshan, a member of the winning team commented:
“This was my first datathon and I felt like I met a number of really cool people with varying educational backgrounds and experience. In particular, meeting Ian (Williams) and learning about the business intelligence and data analytics operations of TPS was eye-opening. Also was able to learn about a lot of cool companies and the ways they are using data science to improve their products and services. Overall, I enjoyed my time and I would definitely participate again!”
Second and third place prizes went to Team H and Team Quantet respectively, with Team D receiving the prize for the best use of SAS.
Congratulations to all the teams who took part and made this such a fun (and competitive) event!
Read about day 1: the kickoff, industry panel, and networking reception
The Master of Management Analytics is designed to give students the advanced data management, analytics and communication skills needed to become an analytics professional.