Data, data everywhere, and nary a data scientist in sight. Or at least, not one you can afford. It's a classic Catch-22. To thrive, businesses need to pull financial, sales, predictive, social, and other data into a complete view of the customer. But big data practitioners with fancy degrees who can bring sophisticated analytics chops to bear on that effort start in the six figures, if you can even find one.
Academics and consultants pontificate on the crisis. McKinsey & Co. exclaims that advanced big data analytics, driven partly by the Internet of Things, could increase GDP in retailing and manufacturing by up to $325 billion annually and trim nearly as much from the cost of healthcare and government services by 2020. Too bad most organizations will never be able to hire that expertise. Yep, the world's got big data envy bad, and a data scientist is the silver bullet we all need.
Here's an alternative viewpoint: You don't need them. Instead, bring big data analytics down to earth, train some people, and use the tools you have, with a few select additions. Now before you go all Pi and post N∞ comments opposing the concept, hear me out.
Read the entire article at InformationWeek http://www.informationweek.com/big-data/software-platforms/analytics-for-all-no-data-scientists-needed/d/d-id/1306607
(Written and researched by Yeoman Technologies' Mike Healey)