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The On-Line Executive Journal for Data-Intensive Decision Support
*** June 9, 1998: Vol. 2, No. 23 ***
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IN THIS ISSUE:
HOW CAN SENIOR EXECS ENHANCE DM'S ROI?
BY INDERPAL BHANDARI
MAXIMIZING DW ROI WITH THE ENTERPRISE DATA MODEL: PART II
BY KATHY LONG
LINKING DM AND PREDICTIVE SERVICES ENVIRONMENTS
BY JOHN THOMPSON
ANALYSIS & COMMENTARY
GOLDEN MEANS: HOW CAN SENIOR EXECUTIVES ENHANCE
DATA MINING'S RETURN ON INVESTMENT?
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: "It has been said that the secret to making a good
speech is to start by describing what you are going to say, say it, and then
close by describing what you have said. In keeping with that advice, I will
expand on a message that has appeared before in this column, namely, the need
to educate the senior executives in an organization about business
intelligence technologies such as data mining."
USING THE ENTERPRISE DATA MODEL TO MAXIMIZE
RETURN ON DATA WAREHOUSE INVESTMENT: PART II
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 this concluding portion of a two-part series, Long observes: "The
challenges in defining the data architecture for warehousing lie in achieving
data integration, promoting information reuse, and providing business
intelligence. The EDM will help define a current and future data architecture
that meets those challenges...One purpose of the EDM is to discover common
threads and develop a cross-functional, common definition of the entity. For
example, a telecommunications corporation manufactures equipment, purchases
equipment for use and resale and develops for sale network management
software that manages equipment. The functional information requirements for
equipment data differ depending on whether equipment is perceived from the
viewpoint of the manufacturing function or the network systems management
function. Is the network switch equipment or product? Does the enterprise
have the same business terms and rules for equipment manufactured, purchased,
and managed via network software?"
Part 1: 100194
LINKING THE DATA MINING AND PREDICTIVE SERVICES ENVIRONMENTS
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: "Previously, I have described how data mining systems are
being decomposed into more granular components of functionality. In this
article, I will describe the initial efforts to build an open standards based
technology that enables the packaging of knowledge gained during data mining
into portable structures. Implied by the description 'portable structures' is
the ability to transport these models between firms and locations. The
transportation of models and ensembles of models will be facilitated by
existing networking capabilities such as the Internet, Intranets, Extranets,
and other communication infrastructures."
ACTION ITEMS
NCR Adds OLAP Services to Extend and Expand Decision
Support Capabilities of Teradata Database
NCR Corporation announced that it has added Online Analytical Processing
(OLAP) Services to its Teradata relational database. NCR's Teradata OLAP
Services provide customers with tools that can be used to perform
multidimensional analysis to discover hidden information within the database.
Teradata OLAP Services will be provided by a new database feature, TeraCube,
and by Teradata Structured Query Language (SQL) extensions for OLAP and data
mining.
University Of Georgia Researchers Help Design
Decision Support System For Forest Managers And Owners
Let's say you own a hundred acres of forest in the mountains of North
Carolina. You want the land to stay beautiful, but you also want to sell some
of the timber to put your kids through college. Years ago, your best bet
would be to cut and pray, but not any more. A new decision support system
that researchers from the University of Georgia have helped design could make
your job vastly easier.
Data Warehouse Designed for Pharmaceutical Executives
Computer Sciences Corporation recently introduced PharmIQ, a data warehouse
service offering that allows life sciences companies to organize sales,
marketing and contract data into a single infrastructure. PharmIQ has been
designed to address the common decision-making needs of a life sciences
company, yet remains flexible enough to accommodate each company's unique
information and analytical requirements.
QUOTE OF THE WEEK
"The purpose of data stewardship is to place the accountability,
control, shareability and quality management of enterprise data in the hands
of the business people who define, create and access the data."
CONFERENCES & SEMINARS 06.09.98
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