As the ability to retain vast amounts of data, examine it and apply findings to further data exercises becomes more and more accessible, establishing policies for effectively going through these steps becomes an increasingly important way of cutting down on invested time, money and energy.

At this year’s HPE Big Data Conference, Chris Selland, VP of Business Development, Big Data Platform, at Hewlett Packard Enterprise Co. (HPE), joined Dave Vellante (@dvellante) and Paul Gillin (@pgillin), cohosts of theCUBE, from the SiliconANGLE Media team, to discuss HPE’s refining approach to Big Data, its uses for customers and the importance of verification.

Checking the quality

Early in the discussion, Selland emphasized the need to consider data sources more thoroughly, questioning their validity and the methods put into their gathering. “Just because you have many data lakes full of data, that doesn’t necessarily mean you have the answer,” he said.

Selland also made the distinction of “applied machine learning” as separate from “machine learning,” with the engagement of users and developers serving to drive the code in more effective ways. “It’s about running models on that data and seeing what impacts what,” Selland said, suggesting that users shouldn’t be carried away by the automation possibilities that are being opened.

In mining these stores of data, Selland continued, there was a need to look beyond the immediate conclusions and correlations, particularly when dealing with customer patterns. “It’s not just variables, but behavior, because we’re talking about people here,” he said.

Expanding the data curve

“The customer stories we hear now are around ‘what we’re doing’ not ‘how much we can store,’” Selland shared. He also noted that while “we are advocates of keeping all of your data,” more needs to be done with looking at gathered data longitudinally, over a stretch of time, instead of limiting the focus to immediately after significant events.

“We’ve kind of really architected what we do to occupy a big part of that curve [of collection ability by users],” he said. “Do we still need to keep everything for compliance? Yes, we do, but it’s really about the learning.”

Selland also noted that at HPE, “we’re doing a lot of work to embed predictive machine learning in our core products” to improve data-gathering and utilization by the customers. And, in addition to that, he said HPE is “really driven by what customers tell us are their most important wants.”

Looking forward, Selland said, “We need to work with the entire cloud ecosystem. … Working with that entire ecosystem is a key part.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the HPE Big Data Conference.

Photo by SiliconANGLE