Executive Briefings

In Era of Big Data, Real Need is for Fast Data

A lot of security processes failed during the breach of Target's systems during last year's holiday season, but one surprising revelation was that the retailer actually did receive security alerts about the malware in its system. Yet because the security team was bombarded with alerts - estimated at hundreds per day - it couldn't adequately prioritize them.

Both within the security field and in other areas, that's a problem that a lot of companies face in the big data era: The top priority is to dig out useful insights from the wealth of data that's coming at them from multiple sources. They're trying to get the right data to the right person at the right time; in fact, the goal is to deliver insights in near real time. The result is a discipline that many in IT are calling "fast data."

IDC analyst Steve Conway explains the challenge this way: "You have to get rid of everything extraneous and do it quickly. Some of it needs to be in real time, like credit card fraud detection. Because if you don’t do it in real time, you don’t catch it." There's also an element of predictive analysis involved in fast data, because you can identify patterns with more recent - and thus more accurate - information.

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Both within the security field and in other areas, that's a problem that a lot of companies face in the big data era: The top priority is to dig out useful insights from the wealth of data that's coming at them from multiple sources. They're trying to get the right data to the right person at the right time; in fact, the goal is to deliver insights in near real time. The result is a discipline that many in IT are calling "fast data."

IDC analyst Steve Conway explains the challenge this way: "You have to get rid of everything extraneous and do it quickly. Some of it needs to be in real time, like credit card fraud detection. Because if you don’t do it in real time, you don’t catch it." There's also an element of predictive analysis involved in fast data, because you can identify patterns with more recent - and thus more accurate - information.

Read Full Article