Students in the University of San Francisco's new graduate analytics program are learning how "Moneyball" math can help some of Silicon Valley's best known companies see patterns in their customers' behavior and make better business decisions with the information.
The term, "Moneyball" math comes from the book of the same name by Michael Lewis. The book was made into a 2011 Oscar-nominated film starring Brad Bitt, which introduced the wider public to the wizardry of sabermetrics—the mathematic modeling that helped the Oakland Athletics acquire high-performing players on a shoestring budget and nearly make it into the 2002 World Series.
Find out more about USF's MS in Analytics Program in a video Q & A with director Terrence Parr.
"Moneyball" to "big data"
USFers in the program learn from experts in business, computer science, economics, and finance, and gain firsthand experience developing complex mathematical models designed to ferret out commonalities in caches of "big data"—information collected by companies about tens of thousands of consumers. The patterns that emerge can provide insights into how costumers use a company's services, where they spend time on a website, what they spend money on, and how those with similar profiles tend to behave.
Retailers depend on data mining to help them predict things like what products will be hot and where travelers want to vacation. Health care providers, such as Kaiser Permanente, like data mining because it has the potential to improve patient care and outcomes, while, at the same time, driving down costs.
"It's such a cool blend of economics, applied mathematics, and computer science," said Spencer Aiello '13, a student in the yearlong intensive MS in Analytics Program. "Plus, it's in the Bay Area and it's only a year long!"
Intern with Silicon Valley's best
As part of the program, Aiello and other students are interning with some of Silicon Valley's best known companies—Pay Pal, Survey Monkey, and media and financial-data firm Thomson Reuters, among them—developing software and running analyses.
"It's a good example of how our proximity to Silicon Valley makes USF a great place to study analytics," said Terence Parr, program director and associate professor of computer science. "All the companies we've approached have been very enthusiastic about gaining access to our interns in hopes of attracting them as employees after they graduate."
The task of analyzing big data can be hard to conceive. More data about people is now created online in just one day than was available on the entire Internet in 2000, Parr said. It's so much that no single computer can crunch the numbers, which is where Amazon.com comes in. With a $10,000 grant from the cloud-computing arm of the world's largest online retailer, USF's analytics students can tap into massive computing resources on-demand, conducting research and completing course assignments.
"Access to Amazon's computing cloud means our students operate in an environment that's the same or very similar to what they'll find industry wide," Parr said.