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December 15, 1997

KPMG Consulting Launches Center for Data Insight at Northern Arizona University
First Data Warehousing Facility to Offer Rapid Testing with Diverse Analysis Tools Mobil Oil Among First to Test at Center

Flagstaff, Ariz. (December 15, 1997 ) —  KPMG Consulting, the consulting arm of KPMG LLP, in partnership with Retrograde Data-Systems and Northern Arizona University, today announced the opening of the Center for Data Insight (CDI), the first academic facility designed to help companies test and develop leading data mining technologies.

Located on the campus of Northern Arizona University, CDI combines KPMG Consulting's business and analytical knowledge with Retrograde's data mining analysis and the University's College of Engineering and Technology and College of Business Administration's technical experience. At the Center, companies can test a combination of tools, from data warehousing to advanced analytical engines, to techniques for visualizing and understanding new knowledge extracted from raw data.

Companies can use up to six different software tools to build and test prototype models for data mining. The new Center allows companies to cut testing time from the typical 12 months to four weeks and use third-party expertise and independent evaluations to evaluate and select appropriate data mining tools.

"KPMG Consulting recognizes the business impact of data mining technologies in transforming company data into corporate intelligence," said Steve Cranford, partner-in-charge of KPMG's Data Warehousing. "The Center is an example of KPMG Consulting's commitment to providing low-risk environments where companies, using their own data, can work through the knowledge discovery process to solve a variety of real-world business problems."

Because no one product has the breadth and depth of all statistical needs, the Center offers clients an opportunity to create specific, business-oriented data mining applications. Without such a testing environment, companies would be required to evaluate disparate vendor offerings and purchase multiple tools, significantly increasing the time and financial investment spent on data mining technologies.

Clients using the Center can load their own data onto servers and utilize a variety of data mining tools for knowledge discovery and management as well as data analysis. Organizations in financial services, retail, and the telecommunications industries can take their own raw data, organize and analyze it, and then employ different modeling techniques such as customer retention and lifetime value models. Currently, Mobil Oil Corporation is using the Center in this capacity.

NAU Provost Charles Connell observed, "The new Center is an excellent opportunity for NAU to provide a first rate education to our students in the very important technical area of Data Mining while providing our faculty with the opportunity to collaborate with KPMG to perform leading-edge applied research for businesses."

Vendor partners include Angoss Software Corporation, Cognos, CrossZ Software, DataMind Corporation, DBStar, ISL Decision Systems, Oracle Corporation, SAS Institute Inc., Silicon Graphics, Inc., Sun Microsystems, Inc., Thinking Machines Corporation, Unica Technologies, Inc., Visible Decisions, and VMARK Software, Inc.

About KPMG Consulting's Data Warehousing Practice
KPMG Consulting is an industry leader in delivering data warehousing solutions that can provide maximum value to clients. Utilizing the firm's comprehensive methodology and extensive technology resources, KPMG Consulting and data warehousing teams assist clients in assessing their business needs and identifying the corresponding enabling technology requirements. In concert with the client, KPMG Consulting professionals can then implement the most effective approach, whether it be a custom data warehouse or an Accelerated Business Solution SM (ABS). ABS is a new service delivery model from KPMG that helps clients implement data warehousing and its allied technologies across the enterprise in less time, with less cost and risk than traditional approaches.



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