Imagine analyzing 10 trillion data points, from a variety of sources, collected at an extremely fast rate. The data can help address business challenges companies faces every day, and possibly even predict client behavior– but you’re not sure where to start. How do you sift through the data that’s available to you, and draw out just the information you need?
Industries we interact with every day deal with this problem regularly, including insurance, transit, financial services, retail and food services, agriculture and health care. With massive volumes of data available, the path forward to practical applications and predictive analysis is difficult to navigate. Companies need someone who can help them build a map; the kind of expertise that researchers at the University of Waterloo can provide.
“Industry and university collaboration is not something that we should just be encouraging people to do. They need to realize that we need to do it – it’s not optional anymore,” says Allaa Hilal, Director of Data Science and Engineering at Shopify, and Adjunct Assistant Professor at Waterloo. “We cannot wait the 10 years, or even five years, that we used to wait until the research comes from industry. We need it today. And working very closely with academia, will allow us to speed the cycle of advancement, and get these innovative solutions faster into our product lines.”
The organizers of the Data Science and Predictive Analytics Academic-Industry Partnering forum wanted to make those connections between business and research. Hosted by the Department of Statistics and Actuarial Science on April 27, with funding provided by a Connect Grant from the Natural Sciences and Engineering Research Council of Canada (NSERC), the event brought together 20 industry partners and 21 researchers to help foster relationships, and encourage collaboration.
“Our goal is to stimulate contact and interaction between companies and academia, and to build on a long history of success in collaborative research,” says Stefan Steiner, Chair of Waterloo’s Department of Statistics and Actuarial Science.
In the morning, industry partners including Fairfax, Loblaw Companies Ltd., and Shopify introduced their companies, and presented some of the challenges they currently face in the areas of data science and predictive analysis.
After lunch, participants engaged in speed networking – similar to speed-dating. Short, one-on-one meetings allowed participants to look for the right match to collaborate on possible projects of mutual benefit.
Participants also received important information about funding opportunities for academic-industry partnerships from NSERC, Ontario Centres of Excellence (OCE), Mitacs, and the Canadian Statistical Science Institute (CANSSI). By connecting problems, experts, data and funding, the event organizers hope to open doors to collaboration on and solutions to real-world problems, with long-term benefits not just for companies, but for the researchers too.
“We’re looking to build research collaborations involving graduate students, over the long term,” adds Steiner. “Seeing your research ideas flow into industry and be used in practice, for a lot of people, that’s really rewarding, and it’s a lot of fun.”