ANALYSIS & COMMENTARY

HISTORICAL DATA: THE FOUNDATION OF DATA MINING, PART I
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 this first part of a two-part article Inmon writes: "The data warehouse consists of historical data, and that foundation serves as a basis for data mining. This seemingly simple statement of affairs appears to be very simple and straight forward. But the relationship turns out to be fraught with complications when the layers of the onion are peeled back."

REAL WORLD EXPERIENCES WITH DATA MINING AND KNOWLEDGE DISCOVERY: PART III
by Jill Dyche & Evan Levy

Jill Dyche and Evan Levy are Partners at Baseline Consulting Group, a consulting firm specializing in data management and database marketing consulting to Fortune 500 companies worldwide.

In this final installment of a three-part series they write: "After three months of using knowledge discovery tools to analyze existing data warehouse data at this company, Baseline was able to identify new and probable marketing opportunities for a variety of customers and products. With only a 1% probability rating, this resulted in an additional $8 million in new yearly revenue. Needless to say, the CIO had more than enough ammunition to move forward with knowledge discovery."

Parts I and II of this series are available as D S * articles 100109 and 100115.

DECISION TECHNOLOGIES IN DATABASE MARKETING: PART IX
by Gene M. Ferruzza, Senior VP, Decision Technologies

For 14 years, Gene Ferruzza has provided integrated business solutions for clients in telecommunications, electric utilities, financial services, aerospace, manufacturing, and retail. He is an internationally recognized expert in strategic database marketing planning and implementation, as well as development and application of data marts, statistical and A.I. modeling, and decision systems for understanding and predicting human behavior. In addition, he directs research in statistical, neural, evolutionary, and hybrid modeling techniques, and the implementation of decision technologies for marketing programs and software productization. He has also developed and marketed his own database management and segmentation software and is currently advising in on-line market research services and products. Prior to CMS, he worked as a consultant and instructor for two leading neural network hardware and software providers (HNC and NeuralWare). Gene graduated from the University of Pittsburgh with a B.S. in Computer Science and Mathematics.

In this ninth installment of an extensive multi-part series Ferruzza writes: "Most data-mining application software packages do not use the data-mart environment directly. They usually operate on flat ASCII files or in proprietary binary environments. So once a sample is extracted, the dataset usually needs to be converted into a format compatible with the modeling tool. For most modeling technologies, the data need to be represented in a numeric format. Unfortunately, the data mart rarely stores all data numerically."

Parts I through VIII of this series are available as D S * articles: 100073, 100080, 100085, 100091, 100097, 100103, 100111 & 100117.

ACTION ITEMS

ISL and SPSS in Partnership To Provide Complete Enterprise Data Mining Solution
ISL Decision Systems Inc., U.S. affiliate of data mining product supplier Integral Solutions Limited, Basingstoke, U.K., announced completion of an alliance with SPSS Inc., a leading supplier of desktop business analysis and data mining software. Under the agreement, the companies will develop an interface between ISL's Clementine data mining product and SPSS data mining and statistics product line, SPSS for Windows.

SIS To Resell Pine Cone Systems Data Warehousing Management Software
Pine Cone Systems, Inc., a leading provider of data warehousing management software solutions, has announced that SIS, a leading value added reseller (VAR) and consulting company in Latin America, has become an authorized reseller and consulting partner for Pine Cone's integrated suite of data warehousing management software solutions.

IBM Details Business Intelligence (BI) Initiative
Top officials of IBM have elaborated on a major business intelligence (BI) initiative, telling reporters in a press conference that the initiative incorporates software and hardware products from throughout IBM, along with extensive worldwide consulting and partnership programs.

QUOTE OF THE WEEK

HISTORICAL DATA: THE FOUNDATION OF DATA MINING: "Examined closely, it is seen that historical data is constantly changing. The constant change of historical data presents the data miner with innumerable problems."
-- W H Inmon

CONFERENCES & SEMINARS 03.10.98

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