ANALYSIS & COMMENTARY

GOLDEN MEANS: DATA MINING AND MEASUREMENT; KEEP YOUR FINGERS FLAT ON THE PATIENT'S WRIST
by Manoel G. Mendonca

This week, Dr. Inderpal Bhandari, executive editor at large, presents a commentary by guest columnist Manoel G. Mendonca -- University of Maryland, Department of Computer Science, A. V. Williams Building, College Park, Maryland, 20742 (electronic mail: manoel@cs.umd.edu ). Dr. Mendonca received his Ph.D. in computer science from the University of Maryland in 1997. He also holds a M.Sc. in computer engineering from the State University of Campinas (1990), and a B.S.E.E. in electrical engineering from the Federal University of Bahia (1986), both in Brazil. His main research interests are on data mining, on the use of measurement for software engineering and management, and on the processes of learning, packaging, and disseminating experiences and expertise in software development organizations. Dr. Mendonca is currently a Faculty Researcher at the University of Maryland where, among other things, he has been working on the use of data mining to analyze software engineering and management data. During his studies, Dr. Mendonca has been a visiting research scientist at the Centre for Advanced Studies at the IBM Toronto Laboratory. Before coming to the U.S., Dr. Mendonca worked as a software engineer in telecommunication and industrial automation industries.

Mendonca writes: "Many years ago, when he still was a pre-med. student, my older brother took my wrist and said, 'Let me take your pulse'. He then laid his fingers on my pulse and after some time he told me, 'Your heart rate is 84 bpm'. Eager to try the procedure myself, I took his wrist, put my fingers on his pulse, and counted his heartbeat. After a brief time, I announced, 'Yours is 164'. He laughed at me and said, 'You did it all wrong. You used the tip of your fingers to take my pulse. This way you counted your pulse as well as mine. You need to keep your finger flat on the patient's wrist.' What does all this have to do with decision making, you might ask. The answer is that all decisions are based on data that are collected, polled, surveyed, sensed, or otherwise measured in some way."

USING THE ENTERPRISE DATA MODEL TO MAXIMIZE RETURN ON DATA WAREHOUSE INVESTMENT: PART I
by Kathy Long

Kathy Long is a Principal Consultant with Spectrum Technology Group. She has enjoyed a diverse career in the information systems field over the past 16 years working as a business analyst, data and process modeler, meta-data analyst, and application designer. She has managed a variety of projects including strategic business modeling, data integration and systems development in the manufacturing, natural gas, pharmaceutical, consumer products and telecommunications fields. As a consultant with Spectrum's data warehousing practice, she has played a lead role in several full-lifecycle data warehouse iterations that defined sales, cost, product supply chain and inventory analytical information. Ms. Long is experienced in data migration design, logical and dimensional modeling, meta-data architecture and analytical information requirements definition.

In the first part of a two-part series, Long notes: "A friend once commented to me, 'I can't justify the investment of developing an enterprise data model to support a warehousing effort. Warehousing is focused on dealing with data at the physical level. I need to move data from a physical source to a physical target. A conceptual enterprise data model is not going to help me in that effort.' I can't argue that source to target data migration analysis and design deals with detailed column domain definitions that are not addressed at the conceptual level. However, I think the enterprise data model (EDM) plays a critical role in the planning, design and future success of the enterprise data warehouse."

COMMENTS AND COMMENTARY FROM THE ROAD
by John K. Thompson

John K. Thompson is the Vice President of Marketing for Magnify, Inc. Thompson has over 15 years experience spanning all major technology management functions for software organizations. In his current role, as Vice President of Marketing, Thompson formulates and executes the strategic direction for Magnify, Inc. and the PATTERN product line. His technology expertise includes knowledge discovery, decision support, data warehousing, and database systems. Prior to joining Magnify, Inc., he held a number of senior technology and marketing positions at PLATINUM technology, IBM, and Metaphor Computer Systems. Thompson has consulted in Latin America, Europe, and Asia regarding the issues around building world class data warehouses and decision support systems. Thompson holds a Bachelor of Science degree from Ferris State University and a MBA in Marketing from DePaul University.

Thompson writes: "The comments that I will paraphrase come from attending seminars that have been vertically focused on specific industries; Magnify & Computerworld sponsored seminars, and the DCI Data Warehouse conference in San Francisco. Trade shows and seminars take up a significant portion of my time, more than I'd like to admit, actually. A few years ago I noticed that there were long spells of boredom punctuated by brief flurries of interest and discussion with a wide variety of people. From these flurries, a significant and useful amount of informal survey data can be collected."

ACTION ITEMS

Computer Concepts Begins Warehousing and Processing Over 8 Million Call Detail Records Per Month
Computer Concepts Corp. (CCC) recently announced that it has begun warehousing and processing, on its recently introduced Internet Server Farm, over 8 million telephone call detail records per month for a Fortune 100 company, and announced also that it will be profitable in 1998.

Carewise, Inc. Links with ThinkMed for Data Mining
CareWise, Inc., a Seattle-based demand and disease management provider, has signed an agreement with ThinkMed, a provider of clinical logic, data mining and decision support software. CareWise will use ThinkMed Expert to target patients for its care management interventions and to assist in measuring the effectiveness of these interventions for its clients.

Auto Supply Chain Achieves Record-Size Data Warehouse at IBM's Teraplex
IBM and Parts America, a 640-store auto parts supply chain, recently scaled the world's largest active data warehouse on an AS/400 at the IBM Teraplex Integration Center in Rochester, Minn., from 275 gigabytes to 510 gigabytes. This is the first time the midrange computer scaled to over one-half terabyte, proving that the platform is capable of analyzing a greater number of variables in larger quantities of customer data.

QUOTE OF THE WEEK

"It is not always clear that the data are fishy."
-- Manoel G. Mendonca, GOLDEN MEANS guest columnist

CONFERENCES & SEMINARS 06.02.98

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