Quinlan teams bring home top honors from Teradata Universe
Quinlan teams have brought home at least one award from the Teradata Universe every year since 2014.
For six years in a row, Quinlan student teams have brought home top honors from Teradata Universe, a global data analytics conference. This year, Quinlan teams won in both student challenges.
The 2020 Student Data Challenge team took home the top award, Most Value to the Client. Team members were Tamera Cawelle, Molly Herdlick, Ines Gonzalez Di Martino, and Shona Sunil.
The 2020 Student Analytics Challenge team won the People鈥檚 Choice award. The team members were Zachary Clark, Laura Cuevas, Michael Esson, Aidan Gregory, and Hannah Niehoff. Both teams were advised by professors Svetlozar Nestorov, Dinko Ba膷i膰, and Nenad Juki膰.
Ba膷i膰 is proud of the students鈥� hard work, saying, 鈥淲e are all excited for the opportunity to represent Quinlan and 黑料门at this international event.鈥�
Working remotely to victory
This year posed the additional challenge of working together in the midst of a global pandemic. At the outset, the Data Challenge team had members across the world 鈥� from Chicago to Rome. When campuses closed and students were sent home in March 2020, members disbursed to Paraguay, Indonesia, St. Louis, and Chicago, creating the additional challenge of juggling time differences.
鈥淚t was crucial for us to come together and find time that worked for everyone to collaborate to analyze the data and create our presentation,鈥� says Molly Herdlick. 鈥淲e all put in the time and worked together to make it happen.鈥�
Tapping into key data insights
This year鈥檚 Data Challenge asked the competing teams to analyze data from the Taproot Foundation, which connects skilled volunteers with nonprofits and NGOs worldwide. Quinlan鈥檚 Data Challenge team was the only undergraduate student team, and the only team from the U.S., to advance to the finals.
鈥淥ur task was to use Tableau to create data visualizations and find insights to further Taproot鈥檚 business,鈥� says Ines Gonzalez Di Martino.
The team soon uncovered a key insight.
鈥淲e noticed that some project categories had fewer completed projects than others,鈥� says Tamera Cawelle. The team鈥檚 recommendation: focus on recruiting additional skilled volunteers for these weaker project categories. 鈥淔or example, we recommended Taproot focus on mobile development projects because that category had a low completion rate.鈥�
Kristi Teti, vice president of program operations at Taproot Foundation, was impressed by the team鈥檚 findings. During the awards presentation, she said, 鈥淭he takeaways were so valuable. You brought the most out of鈥� data that we can take the action on immediately. Based on this鈥� data, you are telling us that we could exponentially increase the impact we are having with this platform.鈥�
The win reinforced the team鈥檚 confidence in their future careers in data science.
鈥淭he data industry overall is still very male-dominated,鈥� says Cawelle. 鈥淲inning the top award as an all-female, all-undergraduate team showed that we were able to rise above and excel.鈥�
Patterns emerged in popular songs
The Data Analytics Challenge team were tasked with finding their own data set to analyze and find key trends and patterns. This year鈥檚 team used data from Spotify, analyzing and data mining over 3 billion Spotify streams.
When the team looked at three top albums and their two most popular songs, they found something interesting. 鈥淭he most popular was the most clicked by users which made sense as people search it out,鈥� says Michael Esson. 鈥淭he second most popular, though, was largely due to Spotify curated playlists. This means that the playlists created by Spotify and other collaborative playlists directly affects the popular and streams of songs.鈥�
The analytics team won the People鈥檚 Choice award, which was voted by hundreds of viewers worldwide during the virtual event.
鈥淲e were excited to be going into the finals following the footsteps of Quinlan鈥檚 teams in past years,鈥� said Esson. 鈥淲inning the People鈥檚 Choice was a great confidence boost.鈥�