Tales of data mining

By Mary Brandel, Computerworld |  Software

When Greg James decided to develop a five-year career plan in the early 1990s, he took out a blank sheet of paper. On it, he wrote down his background, which included large-scale database systems, enterprise system architectures, strategic planning and artificial intelligence. He began drawing lines between the experiences that related to one another, "and data mining was what popped out at me," he says.

That exercise underscores the interdisciplinary nature of data mining and was the start of a successful career for James, who's now pursuing a doctorate in that area while also serving as vice president of information marketing at National City Bank in Cleveland.

As it turns out, there's high demand and low supply for data mining skills today, according to Michael Berry, founder of Data Miners Inc., a data mining consultancy in Cambridge, Mass.

"Many companies are only now waking up to the potential of their vast stores of data," Berry says, and as data mining becomes more common among market leaders, "second-tier companies will want to start mining data in self-defense."

Profile of a Data Miner

Name: Win Fuller

Title and company: Director of marketing analysis, Staples Inc.

Background: A Ph.D. in econometrics, plus seven years as a management consultant and 10 years as a teacher of economics, management science and computer science.

Nature of work: Fuller works in the analytic services group, mining data on a system containing purchase histories for 15 million customers. "If there is a question as to why things are going the way they're going, someone in our area gets called upon," he says.

Typical day: "Questions might come from senior management, like why sales are doing what they're doing or which customers should we be sending direct mail to. Or I might proactively look for trends that trigger other questions from senior managers," Fuller says. "For example, if a particular product is moving faster or slower than expected, I would mine to see which types of customers are buying that product."

Advice: "If you see a void where you're able to provide answers to the business side, don't be afraid to jump in and do it. Not everybody in IS wants to be a techie forever, and this is a route out of that," he says.

What Does It Take?

Data mining involves extracting hidden predictive information from databases to solve business problems. In some cases, analysts mine data for interesting patterns within a segment of the customer base. Then they look for something that might describe why those patterns are happening, James says.

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