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July 6, 2012

Ford Looks to Hadoop, Innovative Analytics

Datanami Staff

After a rocky few years, the American automobile industry is digging its way out from the rubble with a renewed approach to manufacturing, customer relations, and, as you might have guessed, analytics across its wide, diverse pools of information.

John Ginder, who serves as Ford’s Big Data Analytics lead and runs the Systems Analytics and Environmental Sciences team at Ford Research spoke this week about how his company, arguably one of the most data-driven in the industry, is contending with ever-growing, diverse data and the need for solid performance of that information.

He told Jason Hiner that big data offers big promise for a company like Ford, but there is still some “catching up” on the tools and usability end—at least for the mission-critical operations at a global automotive company. There are, however, some notable technologies on the horizon that are helping the automaker boost its ability to make use of vast pools of data, including the Hadoop framework.

Ginder says that the company recognizes that “the volumes of data we generate internally — from our business operations and also from our vehicle research activities as well as the universe of data that our customers live in and that exists on the Internet — all of those things are huge opportunities for us that will likely require some new specialized techniques or platforms to manage,”

He notes that to make use of this potentially valuable data, the company’s research arm is experimenting with Hadoop as they seek to to combine all of these various data sources they have access to.

One of the potential sources of complex data that has clear value for the company lies in their sensor networks. As Ginder stated, “Our manufacturing sites are all very well instrumented. Our vehicles are very well instrumented. They’re closed loop control systems. There are many many sensors in each vehicle… Until now, most of that information was [just] in the vehicle, but we think there’s an opportunity to grab that data and understand better how the car operates and how consumers use the vehicles and feed that information back into our design process and help optimize the user’s experience in the future as well.”

Despite significant progress at experimenting with new platforms and data sources, Ginder also remarked on the lack of tools that are sophisticated, reliable and simple enough to use that the company can democratize big data for wider use. As he told Jason Hiner, “We have our own specialists who are working with the tools and developing some of our own in some cases and applying them to specific problems. But, there is this future state where we’d like to be where all that data would be exposed. [And] where data specialists — but not computer scientists — could go in and interrogate it and look for correlations that might not have been able to look at before. That’s a beautiful future state, but we’re not there yet.”

The end goal is clear, even if the tools have some catching up to do, says Ginder. He remarked on the new world of possibilities that could open up to Ford once they are able to better harness their wells of diverse data. From using camera , sensor and other driver data for uses beyond the driving experience to controlling airflow in the car based on external, real-time data sources, the Ford analytics lead remains hopeful about the future—if not wary of the stability of the newest data handling tools available now.

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