simplystatistics:

Interview with Rebecca Nugent of Carnegie Mellon University.

In this episode Jeff and I talk with Rebecca Nugent, Associate Teaching Professor in the Department of Statistics at Carnegie Mellon University. We talk with her about her work with the Census and the growing interest in statistics among undergraduates.

Harvard Business Review: Data Scientist Is The ‘Sexiest Job Of The 21st Century’ | Popular Science
What is the sexiest job of the 21st century? If you said “data scientist,” you’re probably an editor at Harvard Business Review and probably not anyone else. The HBR has named the emerging practice of sifting through data to find hidden, below-the-surface meaning and otherwise extrapolate underlying knowledge the “sexiest” job of the new century. But while we love Big Data here at PopSci (we dedicated a whole issue to last year), we’re going to have to argue semantics here. Data scientists are certainly in demand (you might even get away with calling it a “hot” profession), but unfortunately that’s not what “sexy” means. It’s an interesting piece, nonetheless. Read it here.

Harvard Business Review: Data Scientist Is The ‘Sexiest Job Of The 21st Century’ | Popular Science

What is the sexiest job of the 21st century? If you said “data scientist,” you’re probably an editor at Harvard Business Review and probably not anyone else. The HBR has named the emerging practice of sifting through data to find hidden, below-the-surface meaning and otherwise extrapolate underlying knowledge the “sexiest” job of the new century. But while we love Big Data here at PopSci (we dedicated a whole issue to last year), we’re going to have to argue semantics here. Data scientists are certainly in demand (you might even get away with calling it a “hot” profession), but unfortunately that’s not what “sexy” means. It’s an interesting piece, nonetheless. Read it here.

Josette Rigsby reports that a recent Jaspersoft study supports the general consensus that there is currently a major lack of skilled Data Scientists. She writes, “Business intelligence platform provider Jaspersoft has released a new survey that examines how companies across the globe are using big data analytics. Although many studies indicate the challenge of managing rapidly growing data volumes paralyzes many companies into inaction, Jaspersoft’s research tells a different story. The data shows 62 percent of respondents plan to implement big data solutions in the next twelve months. Jaspersoft’s new big data survey includes 631 respondents from the company’s user community. The survey includes respondents from more than fifteen countries that are primarily employed by companies with less than US$ 10M in revenue (30 percent).”

In order to solve contemporary business problems, a big data strategy is needed much more than any one product. As I explained in my prior article, “Curing the Big Data Storage Fetish,” there is a growing understanding among enterprises that solving the big data conundrum can’t just be about acquiring more data warehousing technology. To fully exploit the opportunity presented by big data, a value chain must be created that helps address the challenges of acquiring data, evaluating its value, distilling it, building models both manually and automatically, analyzing the data, creating applications, and changing business processes based on what is discovered. Organizations have to figure out a way to increase analytical capacity, not just raw storage capacity.

The hot tech gig of 2022: Data scientist - Fortune Tech
By the end of the decade 50 billion devices will be emitting information nonstop. Data scientists will help manage it all.
A decade from now the smart techies who decided to become app developers may wish they had taken an applied-mathematics class or two. The coming deluge of data (more on that in a moment) will create demand for a new kind of computer scientist — a gig that’s one part mathematician, one part product-development guru, and one part detective.
D.J. Patil is a pioneer in the field of data science, a new discipline that aims to organize and make sense of all the data generated by machines. It’s a challenge that will grow exponentially over the next decade.
Tech in 2012: Face-offs, failures and fairly big changes at the office
Today there are some 400 million devices connected to the Internet, mostly phones and computers. By 2020 some 50 billion devices, from cars to appliances, will be talking to one another. And companies will need teams of data scientists like Patil to sort through everything from internal inventory metrics to customer tweets. The role is so important that Greylock Partners has hired Patil to serve as a “data scientist in residence” to help its portfolio companies mine their data for patterns or stats that will make them more efficient or smarter than their competitors.

The hot tech gig of 2022: Data scientist - Fortune Tech

By the end of the decade 50 billion devices will be emitting information nonstop. Data scientists will help manage it all.

A decade from now the smart techies who decided to become app developers may wish they had taken an applied-mathematics class or two. The coming deluge of data (more on that in a moment) will create demand for a new kind of computer scientist — a gig that’s one part mathematician, one part product-development guru, and one part detective.

D.J. Patil is a pioneer in the field of data science, a new discipline that aims to organize and make sense of all the data generated by machines. It’s a challenge that will grow exponentially over the next decade.

Tech in 2012: Face-offs, failures and fairly big changes at the office

Today there are some 400 million devices connected to the Internet, mostly phones and computers. By 2020 some 50 billion devices, from cars to appliances, will be talking to one another. And companies will need teams of data scientists like Patil to sort through everything from internal inventory metrics to customer tweets. The role is so important that Greylock Partners has hired Patil to serve as a “data scientist in residence” to help its portfolio companies mine their data for patterns or stats that will make them more efficient or smarter than their competitors.