General Electric lays out big plans for big data

Drawing on sensor data collected by GE industrial products, a new wave of analytics will create vast opportunities across a range of industries

In late December, William Ruh, vice president of GE's software and analytics center, described the three key areas of his group's strategy to tackle big data: predictive analytics, a cloud platform for analytics, and security.

As one of the world's largest companies, GE is a major manufacturer of systems in aviation, rail, mining, energy, healthcare, and more. In recognition of the importance of big data to GE, CEO Jeff Immelt launched a new initiative called the "industrial Internet," which aims to help customers increase efficiency and to create new revenue opportunities for GE through analytics.

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The industrial Internet is GE's spin on "the Internet of things," where Internet-connected sensors collect vast quantities of data for analysis. According to Immelt, sensors have already been embedded in 250,000 "intelligent machines" manufactured by GE, including jet engines, power turbines, medical devices, and so on. Harvesting and analyzing the data generated by those sensors holds enormous potential for optimization across a broad range of industrial operations.

As a general example, GE intends to take the warning and error alert data it has been able to harvest the past five years and use it to identify patterns of behavior that lead to more precise scheduled maintenance.

In aviation, the company's GEnx jet engine has 5,000 data points analyzed per second to optimize flight times. For rail, GE and its customers will collect and analyze data from sensors to determine when wheels need to be changed. Also, they intend to add cameras to record video of the tracks that can be analyzed in real time.

GE plans to enrich the data it collects with data from other sources. For example, electrical grid maps will be enriched with satellite data so that utilities know where to cut vegetation to reduce likelihood of power outages during storms.

Ruh says GE will go beyond using existing vendor and open source components. Although the company will leverage Hadoop, R, and more, he also says "no one vendor has the magic bullet." As an example, he points out that machine learning is a particular area that he wants his group to push the envelope beyond what's available today.

To that end, he wants his team to create an analytics cloud so that tools may be plugged in to harvest and analyze the data at will. The platform needs to be flexible enough so that the company can "migrate to the new technology winners as they appear."

Finally, security and compliance are major areas of interest to the company. In particular, the ability to audit who did what when is of critical importance. It extends the forensics available on computer systems to industrial systems.

Ruh notes that scale is a fundamental architectural challenge across all areas. He observes that traditional enterprise software is designed for business transactions and not for the real-time, high-velocity, high-volume data that GE systems generate. As one example, a critical requirement would be storage of time-series data combined with a "Hadoop-style technology" for analytics.

To meet these goals, the company already has a worldwide staff of 9,000 people working in software. But to establish software and analytics as part of the fundamental fabric of the company, Immelt recognized the need to go further.

Immelt has been quoted as saying that GE wanted to establish an office in the Bay Area to more easily hire engineers with analytics expertise as well as to partner with startups in the area. In addition, the company will take equity stakes in some companies in a model similar to its investments in health care ventures.

Two years ago, GE set up its software and analytics headquarters in San Ramon, Calif., near Silicon Valley and recruited Ruh from Cisco to lead the initiative. Ruh says the office has already added 300 people, over half of whom are developers; the rest are architects, marketing, support, and operations people. Ruh expects that total figure to grow to 500 by end of this year.

This article, "General Electric lays out big plans for big data," was originally published at InfoWorld.com. Read more of Andrew Lampitt's Think Big Data blog, and keep up on the latest developments in big data at InfoWorld.com For the latest business technology news, follow InfoWorld.com on Twitter.

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