by Angela Guess
Mary Shacklett recently wrote in TechRepublic, “I recently visited with Shawn Rogers, Chief Research Officer at Dell Statistica, a business unit within Dell’s software group. Rogers predicted a growth in Internet of Things (IoT) big data initiatives in 2016, in addition to an enterprise push for more real-time IoT applications. He said that more big data and analytics applications would move to the edges of the enterprise instead of to a centralized, single data repository, thereby distributing big data pools across the enterprise. ‘I think that 2016 could be the year of the citizen data scientist because users throughout the business want a more democratized approach to big data and analytics,’ said Rogers. ‘Not every company can afford a data scientist, which is a big reason why citizen data scientists will become a big part of the data ecosystem as it evolves’.”
Shacklett goes on, “In April 2015, Gartner research analyst Alexander Linden described citizen data scientists as ‘people on the business side that may have some data skills, possibly from a math or even social science degree — and putting them to work exploring and analyzing data.’ The theory is that true data scientists are relatively rare, expensive ($119,000 is the average annual salary), and that smart business folks with degrees in math or even social science could probably bridge the gap for a lot less salary. To be sure, there are trade-offs. (1) These workers are not likely to have any or perhaps very little background in data analytics. (2) There could be a greater risk of breaches in data compliance, security, and privacy requirements. (3) Lay data scientists could go off on their own to prepare and to interpret data, and come up with strategies that work against those of other business units.”
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