When the Internet became more and more available, some of us “computer geeks” were very proud that we used e-mail long before people even figured out if the word needed a hyphen or not. By the time residential cable and DSL modems became ubiquitous, it was a badge of honor to be running your own e-mail and Web servers at home because back then, you really had to know what you were doing (for the record, I run both in my own on-premise private Cloud to this day - Why? because I *can*).

The massive influx of business users with access to predictive analytics reduces the burden on (typically) overloaded data scientists by freeing them up from some of the more “simpler” problems that could be handled by users directly and letting them work on the more sophisticated predictive problems. Sounds like win-win doesn’t it?
The field of predictive analytics is maturing at its fastest rate ever and the move towards more ease of use and simplicity will eventually reach a plateau, just like standing up a full Hadoop cluster in the cloud can be done in under ten minutes today. The focus will shift from “which is the best algorithm to use when?” to “how I can use these predictive results to improve the business?”. You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.
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