UPDATED 13:31 EDT / OCTOBER 17 2014

Making it look easy: Big Data culture infiltrates GE | #BigDataNYC NEWS

Making it look easy: Big Data culture infiltrates GE | #BigDataNYC

 

Making it look easy: Big Data culture infiltrates GE | #BigDataNYC

Mark Grabb, technology leader, Analytics, GE Global Research In theCUBE

Through innovation and collaboration, General Electric Co. made its transformation to a culture of Big Data look easy. The company’s Global Research team operates under the mission of computing analytics to provide guidance and zero unplanned downtime.

“We have to collect a tremendous amount of information on each asset,” said Mark Grabb, technology leader, Analytics, GE Global Research. “And that data needs to come back and be available for analysis in a very collaborative way so we can create strategic solutions and make decisions about how to eliminate downtime.”

At this week’s Big Data NYC event, Grabb told theCUBE host Dave Vellante that as a result of GE’s vast industry experience, including energy, finance, consumer and industrial, and technology infrastructure, its analytics experts are continuously working shoulder to shoulder with engineers and scientists.

“Our initial challenge was just getting the data together,” Grabb explained. “Then there becomes a rapid tipping point: Once you get your data together, you know where your problems are. And you know your business case. So, now there’s a huge accelerator so you can systematically attack the data issues and make sure you have the right data models in place.”

To assist in its data collection and analytics, GE partnered with Pivotal to create Predix, a software platform for the “Industrial Internet.” Predix enables asset performance management and operations optimization by standardizing data analytics. The software is so successful, GE will make is available to other organizations starting in 2015. “It’s really quite natural. It scales quite naturally with the various GE business units,” Grabb said.

Today, GE has seen a huge shift in its analytics. Instead of spending 80 percent of time just getting the data in order, the analytics team now spends 80 to 90 percent of its time on “the exciting stuff.”

You can catch up on archived interviews on SiliconANGLE’s YouTube Channel here.


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