Who's Training the Next Generation of Data Scientists?
A projected shortage of qualified data scientists could leave U.S. businesses unable to tap the value of big data. To help meet that demand, the University of California at Berkeley has developed a master's degree program to train new data scientists.
Wed, October 02, 2013
CIO — The U.S. faces a projected shortage of 140,000 to 190,000 qualified data scientists - not to mention 1.5 million data analysts - by 2018, according to a study by the McKinsey Global Institute. IT professionals with the skills to analyze big data and guide businesses' decision-making processes will be in high demand and short supply.
The University of California at Berkeley's new School of Information (iSchool) masters' level program aims to help students gain the knowledge, tools and training to land high-level, highly sought-after positions with businesses looking to use big data to improve efficiency, create new revenue streams, and compete more effectively in the marketplace.
Missing: Data Scientists
The new Master of Information and Data Science (MIDS) program is the school's first online-only degree program and is an effort to preemptively address businesses' need for skilled data scientists, says Dean of the School of Information AnnaLee Saxenian.
What's been missing in the market, Saxenian says, is mid-level, master's degree training that can bridge the gap between workers in business who are responsible for collecting the data and the current crop of data scientists, many of whom have Ph.Ds and are working in academia.
"There certainly are folks today in business and in academia who can fill these roles, and they are very valuable," says Michael Chui, principal, McKinsey Global Institute, the research arm of the management consulting firm McKinsey & Company.
"The problem is there aren't enough of them to fill the need. The effective use of data science has applications in almost every business in every organization around the world, and that's the issue," Chui says.
"In the future, we'll be dealing with information not just as text and physical artifacts, but [also as] video, data, audio, sensor data collected from computers, Web clickstream data -- and that will all be globally networked. We are going to need a new education paradigm to address that," Saxenian says.
Above and beyond the new types of data, graduates of the program will be educated in the larger social, economic and personal usage issues that surround data, she says. This new degree program is much more narrowly focused on teaching students to work with data sets of all sizes; to get them to understand how to ask good questions about data; to teach them how to clean it, extract it, put it together and explore it. It's about how to use statistics and machine learning tools, across the whole spectrum of data analytics, Saxenian says.