General Electric(s ge), which has touted the potential advantages of applied big data for a few years and last year put its money where its mouth was with a $105 million investment in Pivotal, is now ready to declare that it has started to reap the rewards.
Using Pivotal’s Big Data Suite and EMC’s(s emc) appliances, GE built out its own capability first for its aviation group in 90 days, which then connected up to 25 airline customers to make use of all that data and analytics, according to Bill Ruh, VP of GE Software, the executive spearheading this effort. GE is a leading builder of aircraft engines and a key goal of using machine data and analytics is to provide better predictive maintenance.
“We want to get away from that alarm fatigue mentality,” Ruh (pictured above) said in an interview. “We want to know when a part is likely to break and watch usage patterns to see how parts can be more efficient and optimized,” he said. In this world, making a gas turbine one or two percent more efficient can add up to huge savings.
Aggregating data from 15,000 flights yielded 14 GB of information per flight, which could then be analyzed in a reasonable amount of time. Some of the lessons learned may seem simple — for example, jet engines that operate harsh, dusty environments need to be washed more often — but that sort of insight can prevent big problems.
Using traditional methods it could take 30 days to sort through data required to figure out a maintenance issue. Now major analytics can be run in 20 minutes, he said. Having all that data — the rows-and-columns of relational data plus the not-so-organized non-relational stuff — in one repository and then being able to access it for analysis represents the “data lake” concept pushed by tech vendors of late.
“This is one of the first and most compelling examples of how customers get value out of data they couldn’t have done in a cost-effective way before –and it shows how much value can be gotten out of disparate data sources,” said Pivotal CEO Paul Maritz.
But it’s not the end at GE. The company’s healthcare division — which makes CAT scanners and other gear — is now rolling out the technology with GE’s power generation, oil and gas, rail and transport groups to follow, Ruh said. The company is integrating its own Predix software with Pivotal’s technology as well.
Clearly GE, with its $257 billion market cap, can afford to pay big bucks for this sort of thing, but Maritz said he expects the technology will also be delivered via a SaaS model in the future so that smaller companies can benefit as well.
For more about Pivotal’s plan to jumpstart new big data applications, check out the video below of Paul Maritz’s talk at Structure Data 2014.