Big Data Quotes of the Week

Atul Butte, associate professor and chief of systems medicine, Department of Pediatrics, Stanford

“In traditional biology research, people ask a key question, or run a trial. They make clinical and molecular measurements to address that question. They use some statistics or computation. Then they validate what they’ve found in another, more advanced trial. I would argue that three out of these four steps are now completely commoditized. We can outsource all that stuff and save a lot of money. But what you’ll never outsource is asking good questions. As scientists, that’s what we’re really supposed to do best. [A lot of the answers to important medical questions are already here, trapped inside a matrix of voluminous data gathering dust in myriad repositories… The trick is to figure out what questions to ask to get the data to divulge their secrets.] I don’t think enough people study the measurements that have already been made. Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world. If I don’t analyze those data and show others how to do it, too, I fear that no one will.”–Atul Butte, Stanford   

“We’re not really here to replace musicologists—I want to stress that, because our old school musicologists get upset by this. But we can change the kinds of questions they can answer. No musicologist could ever listen to 20,000 hours of music. We can get a machine to do that, and find connections that they would miss.”–J. Stephen Downie, University of Illinois, principal investigator of SALAMI

“What we have is data glut. What we really want is the ability to manipulate the information and to reach conclusions from it. I think we are at the point where that is slipping beyond unaided humans’ abilities. So the real thing to be looking for is processing schemes.”—Vernon Vinge

“Hiring data scientists without first having a clear leader in charge of an organization’s overall data strategy strikes me as putting the cart before the horse”– Irfan Khan, Sybase

“A lot of companies don’t know how to find data scientists, and don’t understand data science… enterprise companies can’t implement a proper data analytical solution because they have no data talent….startups are usually much closer to the data they’re analyzing. They know their stuff, and that knowledge is more centralized within a smaller organization.”—Jeremy Howard, Kaggle