Big Data is being touted as the next frontier for innovation, competition, and productivity. It’s widely accepted that leveraging the volumes of data collected electronically will help companies make more predictive, strategic, and evidenced-based decisions to move their businesses forward. Yet, as with any technological development, companies require a specific skill set to take advantage of the opportunity. In the case of Big Data, most organizations lack the talent to effectively analyze the enormous datasets being produced. Ali Behnam, Founding and Managing Partner at Riviera, recently was featured in a PEHub article discussing the demand for “data scientists,” particularly across startup companies.
(PEHub) – The current, accepted wisdom is that those who understand Big Data – the enormous datasets of information being collected with nearly every click of every computing device on the planet – will rule the roost in the future. Presumably, if you can predict behavior by measuring and monitoring people’s machines down to an almost atomic level, you can make both your customers and your shareholders much happier. (See Google.)
There’s just one problem: outside of companies like Google that have long made use of rich rosters of PhDs, there are nowhere near enough “data scientists” — graduate-level candidates with backgrounds in machine learning or statistics — to analyze the massive streams of information that are being produced, and that gap is growing by the day.