IN THIS ISSUE:
GOLDEN MEANS: LIES, DAMNED LIES AND STATISTICS
by Inderpal Bhandari, executive editor at large
Inderpal Bhandari is widely recognized as a leading researcher in data mining and computer science. He is one of the few experts who have successfully demonstrated how the emerging technology of data mining can be translated into useful applications that offer a competitive advantage. Recently, he formed Virtual Gold, Inc. to implement his technical vision. Virtual Gold also offers a consulting service to help clients differentiate themselves from their competitors via the use of data mining technology.
From 1990-1997, Dr. Bhandari was a member of the research staff at the IBM T.J. Watson Research Center, where he received several awards for his pioneering work in data mining and in software engineering. He was the creator and project director of IBM's Advanced Scout, a data mining program used extensively by coaches of the National Basketball Association to devise new strategies based on the automatic identification of hidden patterns in game data and video.
He was educated at Carnegie Mellon University (Ph.D, Electrical & Computer Engineering, 1990), the University of Massachusetts at Amherst (M.S.) and the Birla Institute of Technology and Science, Pilani, India (B.Engg). He has published extensively in leading computer-related journals and conferences and has deployed several cutting-edge technological solutions to business problems.
Dr. Bhandari writes: "Last week, I mentioned that in October 1997 my company, Virtual Gold, Inc., and I hosted a conference entitled "The Evolution of Data Mining: Technical Strategies to Beat your Competition by Year 2000". I then went on to describe some of the new directions that were fostered at the conference. One direction that I forgot to mention is the mining of multimedia data, namely, image, audio and video data. In this article, I build up to a message from the conference on the relationship between data warehousing, digital libraries, and data mining."
DATA MINING WITH THE EXPLORATION WAREHOUSE: PART III
by W H Inmon
Bill Inmon has over 26 years of database technology management experience and data warehouse design expertise, and has published 35 books and more than 300 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing association.
Before founding Pine Cone Systems, Inmon was a co-founder of Prism Solutions. He is responsible for the high-level design of Pine Cone products, as well as for the architecture of planned and future products. Inmon has consulted with a large number of Fortune 1000 clients, offering data warehouse design and database management services. He also worked for American Management Services and Coopers & Lybrand.
Bill Inmon's latest book is Managing the Data Warehouse: Practical techniques for Monitoring Operations and Performance, Administering Data and Tools, Managing Change and Growth, (1997) co-authored with J. D. Welch and Katherine L. Glassey. Publisher: New York, NY: John Wiley ISBN: 0-471-16310-4
In the third and final installment of a three-part series Inmon writes: "There are then many obstacles awaiting the data miner. Having an exploration warehouse as a standard part of the DSS infrastructure allows the data miner to turn the data upside down looking for these important relationships. The exploration warehouse provides the data miner with the infrastructure needed for success."
Parts I & II of this series may be retrieved as D S * articles: 100152 , 100158
THE ROLE OF TPC-D BENCHMARK RESULTS
IN SELECTING A SERVER FOR BUSINESS INTELLIGENCE: PART I
by Daniel Graham
Daniel Graham is Global Strategy and Operations Executive for IBM Global Business Intelligence Solutions. In this first installment of a three-part series, Graham observes: "How important are TPC-D benchmark results in selecting a server? The Transaction Processing Performance Council (TPC) offers three important metrics -- Power, Throughput and Price/Performance. A customer shopping for a server on which to run complex business intelligence tasks must keep up to date on this information. A thorough knowledge of recent TPC benchmarks should be a basic component in any prospective purchaser's decision-making process. However, having said that, a customer must also be aware that many other factors will come into play before he or she can make a final purchase decision."
ACTION ITEMS
Federal Election Commission Approves White Oak
Technologies Plan to Offer Advanced System
for Contributor Data Analysis
In an Advisory Opinion issued today, the commissioners of the Federal
Election Commission authorized White Oak Technologies, Inc. to market its
package of data mining software and services to political campaigns and
committees.
NCR and ISL Strengthen Data Mining Alliance,
Announce Tighter Integration of ISL
Technology with Teradata Database
NCR Corporation and Integral Solutions Limited (ISL) have announced that
the two companies had entered a new phase of their partnership in order to
deliver maximum benefit to customers wishing to mine data from data
warehouses that are built with NCR's Teradata relational database.
U.S. Department of Defense Health Affairs
Selects SPSS for Windows to Analyze
World`s Largest Health Care Data Store
The United States Department of Defense Health Affairs has named SPSS for
Windows as the analytical tool for its Enterprise Data Warehouse. SPSS is
business analysis and data mining software.
"(T)he patterns of a data mining exercise will likely only
capture the gist of the knowledge to be discovered."
-- Inderpal Bhandari, D S * executive editor at large
CONFERENCES & SEMINARS 04.28.98
D S * INFORMATION
D S * welcomes bylined comments for publication.All comments regarding editorial content should be sent to: dseditor@tgc.com