To some engineers at IBM, the traditional approach to software analysis is far too inefficient. Data is collected and stored in a repository, and then software breaks off chunks of it to analyze. Some time later, the software spits out a result. But recent work at IBM is providing a better way: analyze the data as it's collected. The concept is called stream computing and it could revolutionize industries like finance, health care, and weather monitoring, where real-time data and analysis can help people make better, faster decisions.

In April, IBM showed off a system that could analyze the constantly fluctuating value of stocks. Now the company is working toward developing a product, called System S, that could be applied to any field in which numbers need to be crunched quickly.

According to a recent New York Times story:

I.B.M., based in Armonk, N.Y., spent close to six years working on the software and has just moved to start selling a product based on it called System S. The company expects it to encourage breakthroughs in fields like finance and city management by helping people better understand patterns in data.

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Instead of creating separate large databases to track things like currency movements, stock trading patterns and housing data, the System S software can meld all of that information together. In addition, it could theoretically then layer on databases that tracked current events, like news headlines on the Internet or weather fluctuations, to try to gauge how such factors interplay with the financial data.