Some Data Scientists Have Never Seen a Mainframe: Is That Possible?
Bryan Smith, CTO and VP of Rocket Software, is a frequent guest blogger here at EnterpriseSystemsMedia.com. Recently, he had the opportunity to strut his mainframe stuff before an audience of data scientists who, believe it or not, knew next to nothing about the mainframe. In the article below, it sounds like Bryan had a blast.
Rocket Software Talks Mainframes With Data Scientists Who’ve Never Seen One
By R. Danes
A chief technology officer walks into a tech conference and approaches some data scientists. He asks them how they begin their analytics processes. They all say, “ETL.” He tells them ETL (extract, transform, load) is dead; mainframes are the future. They burst into laughter.
Well, maybe they didn’t laugh, but the data scientists Bryan Smith, chief technical officer and vice president of Rocket Software Inc., spoke with at last week’s AnacondaCON event were certainly surprised.
He related the story today during the IBM Machine Learning Launch Event in NYC.
“I told them ETL is dead, and they just kind of looked at me kind of strange,” Smith said in an interview with Dave Vellante (@dvellante) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio.
Smith said he enjoyed educating them about what a mainframe is and how it relates to the ETL issue. “ETL’s future is very bleak,” he said, explaining that the process is too slow for real-time or near real-time analytics. “It had its time, but now it’s done, because now you can access that data in place.”
To that end, Rocket Software has just launched a product called Rocket Data Virtualization. “Data Virtualization is really enabling customers to open up their mainframe to allow the data to be used in ways that it was never designed to be used,” he said.
Smith said that instead of copying the data and moving it out through ETL, data virtualization allows developers to access it with APIs. And they are not limited to data in the mainframe; they can pull in outside data from social or other feeds.
Developers Give the Verdict
Smith said that this approach is easier than shipping gargantuan data around in cyber space, and this will ultimately win over the developers and data scientists. It is they who make the market at the end of the day, according to Smith.
“Give them what they want. They’re the customers of the infrastructure that’s being built,” he said.
This article originally appeared on the SiliconANGLE Website on Feb. 15, 2017. The original post is available at http://bit.ly/2lTB8gW.