The most significant results might lie in the intersections of each model's results, and you need a thorough understanding of the algorithms to interpret them, he says. Banks that have made serious investments in data mining typically employ several people trained in statistical analysis or applied mathematics. So while data mining specialists extol the virtues of the technology in one breath, they caution about its complexity in the next. It doesn't sit in your computer, find things in your databases and tell you what to do with them. Data mining can be downright tedious, Mrazek says.
Some models can take several months to complete.
But, like gazing at one of those 3-D posters, persistence pays off. Those images reflect higher profits. Consequently, some people think that data mining is an automated process that doesn't require sophisticated analysis. That's an illusion. ERP systems are notorious for making databases difficult to manage because it's tough to selectively delete data.