From computertrainingschools.com
Industry, Universities Rush to Fill Big Data Skills Gap
By John Mello
According to an estimate by Gartner, by 2015 4.4 million global IT jobs -- 1.9 million of them in the United States -- will be created in support of big data initiatives.
That rapid growth is creating a pressing demand for big data professionals -- a demand that will be difficult to meet. "There is not enough talent in the industry," Gartner senior vice president Peter Sondergaard said in a statement issued during a symposium in 2012. "Our public and private education systems are failing us. Therefore, only one-third of the IT jobs will be filled."
Since Sondergaard aired his analysis of the job market, however, companies like IBM and higher education institutions like the University of California, Berkeley and Boston University have started to step into the breach to meet the challenge posed by the big data talent gap....
UC Berkeley's big data education push
Breadth was taken into account when UC Berkeley designed its Master of Information and Data Science program.
"There's a whole lot more to the landscape of what the skill set is of what we think is necessary to be a true data scientist that isn't wrapped up in a discipline like computer science," said Coye Cheshire, associate dean at Berkeley's School of Information.
For example, the Berkeley program places a heavy emphasis on stating problems and constructing questions for a big data project. "That's a fundamental skill that a lot of people lack," Cheshire said.
"A lot of people wait for the data to kick back answers," he continued. "We don't approach data science that way. We want to go in with knowledgeable questions and we want to know how we can use the data in an intelligent fashion."
That approach led the school to add courses on research design and problem generation -- courses not typically found in a data science program. There are also more traditional disciplines -- statistics, working with R, programming, data bases, machine learning and field experimentation.
Berkeley's curriculum reflects a distinction it sees between big data and data science. "A lot of people think big data is data science," Cheshire said. "We believe data scientists should be knowledgeable with working with problems and working with data. They're not just data analysts. They're people who can set up good questions and figure what kind of data they need -- whether it be enormous data bases worked on in clusters or experimental data where A/B testing is needed."
In addition to hard information science courses, the Berkeley program also includes policy courses. "We teach classes on information privacy," Cheshire said. "You won't see that in other degree programs."
Another unique aspect of the program is that it's offered entirely online. "We wanted to make something that was accessible for people who are already working professionals," Cheshire explained.
The program is designed to be as close to an on-campus program as possible, however. Applicants go through the same admission process as classroom students. Classes are kept small -- 15 students or so. In addition to programmed learning, live video classes are held every week. Professors even have office hours for students....