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Data mining event features world-renowned thought leaders, best practices

SAS recently hosted M2004, its seventh annual data mining analysis and applications conference in Las Vegas. Nearly 800 data mining experts and practitioners gathered at M2004, breaking attendance figures for the sixth consecutive year and, for the first time, establishing it as the world's largest data mining conference.

Given the exciting venue and outstanding lineup of speakers, it's no wonder that the conference attracted so many attendees. The attendance figures, announced this week, represent a 30 percent increase from last year's high of 610 attendees. Participants came from 40 different states in the U.S. and more than 20 nations.

M2004 - with the help of four distinguished data mining thought leaders, 10 session track topics and more than 45 speakers representing the corporate, government and academic worlds - featured "best practices" in the field, as well as some of the latest technological advances.

This year's keynote speakers featured four highly regarded data mining experts:

• Andreas Weigend, former chief scientist for Amazon.com and an encore keynote presenter from last year's conference, spoke about "Online Customer Behavior."
• Trevor Hastie, distinguished professor in statistics and biostatistics at Stanford University, presented "Least Angle Regression, Forward Stagewise and the Lasso."
• William DuMouchel, technology consultant for AT&T Labs, gave an address on the "Empirical Bayes Methods for Postmarketing Surveillance of Adverse Drug Reactions."
• Bill Kahn, chief scoring officer for Capital One and the first keynote speaker to take the stage, spoke on an intriguing topic: "Why Data Mining is Not Used and Why Better Data Mining Won't Help."

M2004 was co-chaired by Michael Hardin, director of the Institute of Business Intelligence with the College of Business at the University of Alabama, as well as a professor of statistics there; and Jerry Oglesby, director of SAS' Higher Education Consulting group.

Knowledge shared beyond the conference

Immediately following the conference, 293 participants remained in Las Vegas to attend one or more post-conference training courses. Participants chose from several courses, such as "Advanced Data Mining Techniques," "Advanced Predictive Modeling," "Mining Textual Data Using SAS Text Miner for SAS(r)9," and "Predictive Modeling Using SAS Enterprise MinerTM 5."

What makes the M-series of conferences so appealing, many attendees agreed, is its balance between theory and practice. M2004 offered everyone in attendance - from the novice to the most experienced data miner - new ideas, best practices and a glimpse of what the future holds for data mining.

"I've only been here eight hours and have already increased my knowledge exponentially," said Dr. Jody Porrazzo, long-time SAS user and the director of econometric risk strategy for APEX Management Group, a leading healthcare consulting and insurance services organization. "And, I've already made two valuable contacts - one is a woman who's performing the same type of analysis we're doing. I'm going to visit her company to see how they're doing it."

Adam Fadlalla from Cleveland State University said this was his second year attending the conference, and he plans to return again. "M2004 covers more of an applied, or real-life, perspective. The training that comes with the conference is also a big attraction, as well as the opportunity to meet and talk to the people from SAS."

M2005 again scheduled for Las Vegas

SAS has already scheduled next year's conference, M2005, once again to be held in Las Vegas. Scheduled for Oct. 24-25, 2005, M2005 will build on the foundations of M2004 and will offer a similar lineup of world-renowned industry experts discussing the latest data mining trends, theories and best practices. Conference co-chairs have already been named: Jerry Oglesby, director of Higher Education Consulting at SAS, and Michael J.A. Berry, co-founder and principle consultant of Data Miners Inc.

Wayne Thompson is manager of strategy for data mining and analytics at SAS. He can be reached at wayne.thompson at sas.com .