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Data Mining: Changing the Face of Disaster Response

TornadoHere’s another great example of how a well-constructed data mining and predictive analytics project can provide actionable insights which solve major problems. Disaster management teams are now using predictive analytics to improve responses and outcomes during major crisis events.

The team points out that advances in information technology have had a profound impact on disaster management. First, these advances make unprecedented volumes of data available to decision makers. This, however, brings with it the problem of managing and using that data. The team has surveyed the state of the art in data mining and machine learning in this context. They have found that whereas earlier applications were focused on specific problems, such as modeling the dispersion by wind of plumes – whether from a chemical plant leak, fire or nuclear incident – and monitoring rescue robots, there are much broader applications, such as constructing situational awareness and real-time threat assessment.

Alpha Galileo

This is an incredible use of data mining.

When you look at incredible applications for data mining like this it can become even more frustrating to watch organizations squander opportunities by launching expensive projects that are destined to go nowhere fast.

That’s why TMA offers the free webinar: Data Mining, Failure to Launch. It’s also the purpose behind TMA’s training courses.

Whether you’re tackling chemical dispersion patterns or improving your distribution process, it’s important to focus on strategy first. That way, you can get the results that you want–results that help you do more, just as these disaster response teams are.

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