There’s a popular statistic in the world of big data, that 90 percent of the world’s data, measured since the dawn of recorded history, was produced in just the last two years. That was in 2013. More recent estimates suggest the world is doubling the size of our data every two years. It floods in from everywhere: from the financial transactions of banks and the electronic medical records of health care providers, and from the smartphones, social media accounts, and Google searches of the more than four billion of us worldwide connected to the internet. We shed information like cats shed fur. (Speaking of cats, there are an estimated 6.5 billion pictures of them online. That’s data, too.)
Even though generating data has long been relatively easy, being able to make smart use of it has been a different story. We just haven’t had the computing power. “There are many data sets that we’ve been collecting for twenty or thirty years which are just now getting into use because there are now the tools to understand them,” said Computer Science Professor Alva Couch.
The development of new tools is requiring a new kind of expert to harness their power: the data scientist.
“Data science is a marriage between statistics and computer science,” Couch said. By blending the decision-making focus of statistics with machine learning and artificial intelligence from computer science, data scientists are learning how to make smart decisions like never before. Companies like Google and Amazon are using data science to better serve customers what they want, when they want it. Farmers are improving agricultural production and crop resiliency, medical researchers are hunting better treatments for patients, and municipalities are studying everything from traffic patterns to crime statistics to make our communities safer. And that’s only the beginning of what you can find when you know how to look.
“[Data science] allows us to see the unseen,” Couch said. “To see small trends and things that we might not consider, but which are actually very significant.”
Preparing Data Scientists for the Job Market
Experts trained to handle the analytical tools of big data are in tremendous demand. Job postings for data scientists have skyrocketed by 256 percent since 2013, according to the employment site indeed.com. Harvard Business Review has called “data scientist” the “sexiest job title of the twenty-first century.”
To best prepare students for this new career, Tufts recently launched a new data science degree track for undergraduates. Codirected by engineering professors Alva Couch and Shuchin Aeron, the program harnesses the university’s interdisciplinary strengths by requiring students to take not just the traditional math, computer science, and computer engineering courses, but also coursework in applied areas like biology, global health, and water security.
“The purpose of the data science field is to make real-world decisions,” Couch said, whether that’s on behalf of a company or broader interests. “To [be able to] say, ‘If I make this decision, I’ll pollute the air, but if I make this other decision I won’t.’” Enthusiasm for the new track is already running high among undergraduates.
This fall, Tufts will also kick off a data science master’s program, geared to professionals eager to return to school to further their careers. “They already have good jobs in software engineering, but they’re seeing the value of getting a data science education too,” Couch said. “Data science has become a more attractive and versatile job than software engineering, and it puts scientists closer to making the decisions that empower a company, and closer to upper management.”
A Sample of What the world does online in a single Minute
Forecast requests made to the Weather Channel
Songs streamed over Spotify
Hours of Netflix video streamed
Photos posted to Instagram
Source: “Data Never Sleeps 6.0,” Domo, Inc.
Shannon Fischer is a freelance writer and frequent contributor to Tufts Magazine. Send comments to firstname.lastname@example.org.
More on Next-Gen Computer Science: