Big data software makers are throwing every possible technology at the business insight and monetization problem with little success. Perhaps taking a step back from machine intelligence to human intelligence would yield better results.

“The science experiment phase of the big data world is over; people now have to show a return on investment,” said Nenshad Bardoliwalla (pictured, right), co-founder and chief product officer of Paxata Inc.

Bardoliwalla joined Stephanie McReynolds (pictured, left), vice president of marketing at Alation Inc., spoke with John Furrier (@furrier), co-host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the recent BigData NYC event in New York. They discussed the evolution of data for business intelligence. (* Disclosure below.)

“In the world of data warehousing, business people are told what data they should use,” McReynolds said. In this typical scenario, the information technology department will decide how to model data and then hand down prefab guidelines to business people. The parameters that IT people set for business executives often don’t leave leeway to make creative decisions on the fly.

This paradigm is shifting. Big data frameworks like Apache Hadoop allow on-demand data structuring and encourage more iterative exploration, McReynolds explained. “The only challenge is without simplifying that process, a business person is still lost,” she said.

Behavior I/O

Within a large data lake, files may be unlabeled, which can make analytics confusing and time-consuming. Alation puts metadata — comments, observations, annotations from users — around files to provide some intel on their contents. Paxata and Alation have integrated so that Alation users can click on a file and immediately go to Paxata and see the actual contents of the file.

“So you can very quickly go from ‘this looks interesting’ to ‘let me understand what’s inside of it,'” Bardoliwalla said.

“The fact that behavior of how people query data is an input, and that input then informs recommendation as an output is very powerful,” McReynolds said. She calls this method “behavior I/O.”

A growing number of big data practitioners are coming to appreciate human-tech synergy, McReynolds added. “This acknowledgment that there should be balance between a given input and what a technology can do is a nice breakthrough that’s going to help us get to the next level,” she said.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of BigData NYC 2017. (* Disclosure: Alation Inc. sponsored this segment of theCUBE. Neither Alation nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE