ANALYSIS & COMMENTARY

METADATA AND DATA MINING: TWO UNLIKELY PEAS IN A POD, 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 segment of a two-part commentary, Inmon notes: "The relationship between data and data mining is clear. Data mining cannot be done unless there is data. But the relationship between metadata and data mining is not nearly so clear. Although it is hardly obvious, there is a strong and important relationship between the activity of data mining and metadata."

WHY DATA MINING?
by David Danziger, Trajecta

David Danziger is a Marketing Associate at Trajecta, Inc., a data mining and optimization company headquartered at Austin, Texas. Danziger writes: "A major long distance company (lets call them Company A) recently contacted me. This company offered me $100 to switch from another carrier (which we'll call Company B). I had previously been a customer of Company A, and only switched to Company B because they offered me 5,000 bonus miles on my favorite airline's frequent flyer program. Why the offers? Do these companies know something about me? Absolutely, and they know it as a result of data mining."

DECISION TECHNOLOGIES IN DATABASE MARKETING: PART XI
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 final installment of an extensive multi-part series, Ferruzza observes: "...(P)arametric and non-parametric modeling technologies are data-driven processes; the data are used to tune the parameters in the model. Today, the process of collecting and storing data is highly efficient. Any active database is likely to be changing at least monthly, if not daily, hourly, or even in real time. This means that the customer data at any given moment differ from the data that were used to develop the model -- as do the customers themselves (as a result of customer acquisition and attrition)."

Parts I through X of this series are available as D S * articles 100073, 100080, 100085, 100091, 100097, 100103, 100111, 100117, 100123 & 100129.

ACTION ITEMS

SAP Announces New Direction and Tech Architecture
SAP's co-chairman recently outlined a major new direction and technology architecture for SAP. Rather than building tightly integrated, transaction-oriented applications around a single database, SAP will begin to link R/3 with a series of loosely coupled, DS-oriented applications that users can run as stand-alone modules.

Pine Cone Systems Announces "Pine Cone Enabled" Partner Program
Pine Cone Systems, Inc., a leading provider of data warehousing administration and management solutions, has announced an innovative partner program that allows leading OLAP vendors to integrate Pine Cone's Usage Tracker software, which monitors and reports on data warehouse activity and usage, into their data access and analysis software.

Platinum Technology to Acquire Data Modeling Leader Logic Works
Platinum Technology, Inc. has announced it has signed a definitive agreement to acquire Logic Works, Inc., which offers one of the industry's best-selling data modeling solutions. Together, Platinum and Logic Works will offer a comprehensive solution for modeling application components, databases and business processes. The combined offerings of both companies will provide a solution for application developers, database administrators and data warehouse managers.

QUOTE OF THE WEEK

WHY DATA MINING? "The critical piece of the puzzle for marketers of all stripes, whether direct or retail, is understanding what marketing mix will yield the best possible results in the customer universe."
-- David Danziger, Trajecta

CONFERENCES & SEMINARS 03.24.98

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