It’s slim pickings out there for those seeking highly skilled data talent. Even as universities introduce data science tracks and organizations spring up to enable networking, the average enterprise still struggles to juice the work of 10 data scientists out of the one or two they may have on deck. Until the output of the academies and training grounds catches up to the demand of the real world, companies will have to look for software tools that think and act like flesh and blood data scientists.

Ritika Gunnar, VP of Data and Analytics at IBM, spoke to Dave Vellante (@dvellante) and George Gilbert (@ggilbert41), cohosts of theCUBE, from the SiliconANGLE Media team, during BigDataNYC 2016 about what she calls “insight ops” — the process of collapsing the insight-to-application process into a smaller package to get the most from data talent.

“Where your data science professionals are actually finding new golden nuggets, when you want to operationalize those into production like environments, and you want to do that seamlessly … it’s about insight operations,” Gunnar  said. “Some may call it data ops; we call it insight ops.

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Tools that help data scientists and developers collaborate efficiently are invaluable for extracting value from data, Gunnar said.

“That collaboration that needs to happen between a data science professional that is driving and finding those insights and the application developer who is codifying that in their web and mobile applications — that collaboration needs to happen in real time, so that you can realize the benefits within your application quickly,” she explained.

The big blue button

In its presentation tonight, IBM will demonstrate how its technology cuts down the time it takes to operationalize insights. It will show how its “takes insights that we’ve developed through an R model and we actually infuse that into an application that has been built within Bluemix [IBM’s hybrid cloud development platform} seamlessly in the snap of a button,” she said.

IBM will also be making announcements about Watson DataWorks (cloud-based data refinery) and the data-first method.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of BigDataNYC 2016.

Photo by SiliconANGLE