ANALYSIS & COMMENTARY

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 concluding segment of a two-part article Inmon writes: "The changing nature of data, especially at the detailed level, presents an intriguing story when viewed over time...The classical approach to the amendment of data over time (or the restatement of data over time) is to go back and alter the detailed data, and do a recalculation based on the amended data. The process to do restatement at the detailed level is tedious and extremely resource intensive. In every case."

Part I of this series is available as D S * article 100121.

Kurt Thearling is Director of Advanced Analytics at Exchange Applications, a Boston-based database marketing company, where he directs the use of data mining and visualization technology in EA's database marketing software and consulting practice. Over the past decade he has developed a number of commercial data mining software products, including Thinking Machines' Darwin and Pilot Software's Discovery Server. He also an independent consultant in areas related to data mining and decision support technologies. His data mining web page can be found at http://www.thearling.com

Thearling observes: "In recent years privacy concerns have taken on a more significant role in American society as merchants, insurance companies, and government agencies amass warehouses containing personal data. The concerns that people have over the collection of this data will naturally extend to any analytic capabilities applied to the data. Users of data mining should start thinking about how their use of this technology will be impacted by legal issues related to privacy."

DECISION TECHNOLOGIES IN DATABASE MARKETING: PART X
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 tenth installment of an extensive multi-part series Ferruzza writes: "Simplification of the data also can be important. In contrast to normalization, which ensures that we don't lose information, simplification allows us to eliminate data that hold no value for the model. For example, EDA may indicate that it is important to know whether or not the individual is MARRIED, but that no further benefit is gained from knowing whether the customer's marital status is SINGLE, DIVORCED, or UNKNOWN."

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

ACTION ITEMS

Hitachi and Prism Join Forces in Data Warehouse Solution
Hitachi, Ltd. and Prism Solutions, Inc., a leading supplier in the data warehouse market, have announced a major partnership in the area of data warehouse products for the Japanese market. Under the partnership, Hitachi aims to achieve leadership in the Japanese market by integrating Prism's products.

Sears Manages Data Warehouse With EMC Enterprise Storage
EMC Corporation, a provider of enterprise storage systems and software, announced that Sears, Roebuck and Co., the largest department store chain in the U.S., has deployed more than fourteen terabytes of EMC's Symmetrix Enterprise Storage to support a data warehouse providing timely sales and inventory data for 2,700 Sears managers, buyers, and other users.

Sequent Unveils Roadmap for Integrated UNIX and Windows NT in the Data Center
Sequent Computer Systems, Inc. has outlined a three-year roadmap delivering on the promise of NUMA and declaring the end of tough choices between operating systems and architectures for deployment of mission critical applications.

100127 "There are then some powerful reasons not to restate historical data at all. Indeed, at some point in time the volume of data that must be passed during the restatement process precludes historical restatement."
-- W H Inmon

CONFERENCES & SEMINARS 03.17.98

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