Communications of the ACM
More Training, Skills Development Needed For Analyzing Big Data, Experts Say
Credit: Trifects
Big data training is a major challenge, according to a recently published study from the National Academies Press. The report says students must learn how to best use big data, and it states the need to better educate students at universities, better understand what goes into analysis, and use alternative methods for training.
People who work in data science need a broad set of skills, including knowledge of randomness and uncertainty, statistical methods, programming and technology, as well as practical experience, says University of California, Davis professor Duncan Temple Lane. He says students should learn how to plot general questions to a statistical framework and understand the scope of sampling and biases, exploratory data analysis, and diagnostics.
Some institutions offer alternatives to degree programs, such as boot camps, certificate programs, and online courses. For example, the University of Washington's eScience Institute offers a nine-week massive open online course that concentrates on the background of data science, data manipulation at scale, analytics, virtualization, and graph and network analytics. Approximately 7,000 people have earned a certificate from it so far.
The National Academies Press study estimates eight universities have unveiled big data training programs this year, and the total now stands at about 30.
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