SAS’ data mining conference empowers professionals

Enhancing predictive analytics expertise improves attendees’ market value

CARY, NC . – The largest data mining conference of its kind, M2009 takes place Oct. 26-27 at Caesars Palace in Las Vegas. The conference and exhibition is now in its 12th year. Pre-conference activities on Oct. 25 include an introductory course, customized data mining workshops with SAS experts, and the SAS® Certification Predictive Modeling Exam. Several post-conference classes Oct. 28-30 provide a range of professional growth opportunities. This is the venue for exchanging ideas with data mining practitioners and with the world’s most respected data mining experts as speakers. Attendees who register for M2009 by Sept. 18 receive a $200 discount as well as a free data mining book as a registration giveaway.

Organizations accumulate huge volumes of data. Data mining uncovers previously unknown trends and patterns in that data to support decision making. Text mining applies the same analysis techniques to text-based documents. Expertise in predictive analytics can advance careers. “Data mining is becoming more and more accessible to business users,” said William McKnight, a data management expert with US Analytics. “The barrier to entry is lowering and the job is becoming more consultative with the business. It’s a wise career move to master the data mining techniques offered through conferences and training such as at M2009.”
Maximizing data mining benefits

Co-chairs Jerry Oglesby, SAS Director of Global Academic Programs and Certification, and Dirk Van den Poel of Ghent University highlight the latest research and methodology through case studies and advice on maximizing data mining benefits. By upgrading analytics skills and better understanding the latest analytics trends, practitioners can improve decision making within their own organizations.

“Critical during a struggling economy, data mining solutions offer incredible opportunities for companies to improve their bottom line,” said data mining expert and author Olivia Parr-Rud of OLIVIAGroup. “Hiring talented analysts is key to successful predictive analytics implementations. However, increased complexity and the constant introduction of new technologies as well as shifting markets and consumer demands require us to master a broader set of skills. M2009 will give analysts important new theoretical and technical insights as well as practical implementation tips.”

To balance theory and practice, the conference offers six keynotes and more than 35 sessions in tracks including financial services, healthcare, emerging technologies, text mining and marketing research. Demo theater presentations, poster presentations and exhibits highlight innovative work in data mining.

Keynote speakers include:

* Bart Baesens, Professor, Faculty of Applied Economic Sciences, K.U. Leuven (Belgium) and the School of Management, University of Southampton (UK), researches data mining, credit scoring and Web mining.
* Michael Berthold, Nycomed-Chair for Bioinformatics and Information Mining at University of Konstanz, studies using machine learning methods to analyze large information repositories in life sciences.
* John Elder, CEO, Elder Research Inc., operates a data mining consulting firm focused on investment, commercial and security applications of advanced analytics.
* Manfred Krafft, Marketing Chair, University of Münster, is noted for work in customer relationship management, direct marketing, and sales management.
* Kim Larsen, Advanced Analytics Group Director, Charles Schwab & Co., specializes in customer segmentation, forecasting, price optimization and predictive modeling.
* Will Neafsey, Brand DNA and Consumer Segmentation Manager for Ford Motor Company, has worked in market research, new business creation and incubation, information technology, operations research and manufacturing.

Annual Data Mining Shootout

The Central Michigan University Research Corporation and Dow Chemical again team with SAS to offer the academic community an opportunity to test their data mining skills. The third annual Data Mining Shootout lets student and faculty teams distinguish themselves by solving a real-world data mining problem.