The Data Management Association
Sacramento Valley Chapter
Presentation:
"What's
Wrong with ER Modeling?"
or
"Overcoming the Limitations of ER Modeling"
Speaker:
Dr. Gordon C. Everest
Professor Emeritus of MIS/Data Management,
Carlson School of
Management - University of Minnesota
Time:
Tuesday, October 23, 2007, 9 A.M. - 11P.M.
Location:
California Public Employees' Retirement System (CalPERS) Headquarters
Lincoln Plaza Building North
400 P Street, Rm 1170
Sacramento, CA Driving DirectionsParking Options
Cost:
There will be a fee for non-members of $20 and
$15 for students. Renewing members do not need to pay this additional
fee.
RSVP:
Please RSVP to the Programs Director at
(916)323-1461 or corinna.martinez@cdcr.ca.gov
to ensure enough handouts
and space.
Synopsis:
Entity Relationship (ER) data modeling goes
back to a paper by Peter Chen in 1976. He proposed a data model
diagramming scheme which would transcend thinking about physical records,
by focusing on the entities and their interrelationships in the users'
real world domain of interest being modeled in a database. When
relational DBMSs came on the scene, ER Diagramming was a good and natural
scheme for designing relational databases. Today, ER Diagrams and
Relational DBMSs are widely used
throughout the world in the development of computer-based information
systems.
Data modeling is the foundation of information systems development - if
you don't get the database design "right" then the systems
you build will be like a house of cards, collapsing under the weight of
inevitable future forces for revision, enhancement, integration, and
quality improvement. Therefore, we need a scheme to guide our data
modeling efforts which helps produce data models that are a clear and
accurate representation of the users' domain of discourse, and which
facilitate human communication, understanding, and validation.
Many popular data modeling schemes and supporting design (CASE) tools in
use today are essentially variations on ER Diagrams, including Teorey's
Extended ER, Finkelstein's Information Engineering (IE, and adapted by
Martin), Appleton's IDEF1X used by the U. S. Government, Barker in
Oracle Designer*2000, PowerDesigner from Sybase, ERwin now from Computer
Associates, Kroenke's Semantic Object Model (SOM), and even UML Class
Diagrams. This talk could equally be entitled, "What's Wrong with them?"
To answer the "What's Wrong..." question, we need to begin by asking:
* WHAT are we trying to do in Data Modeling?
* WHY do we do data modeling? - the purpose and objectives.
* HOW do we do data modeling? - what drives or guides the process?
* By what criteria do we judge or evaluate a data modeling scheme?
* What is the essential, distinguishing characteristic which underlies
all
ER modeling schemes?
* How well does ER modeling satisfy the criteria for a good data
modeling
scheme?
Think about these questions. Then we will try to come to some consensus
before launching into a discussion of what's wrong with ER modeling,
backed up with several examples. Having convinced you that there is a
problem, we will point you in the direction of a solution -- a better
way of doing data modeling.
This talk argues that the distinction between entities and attributes is
artificial, hence troublesome for the data modeler, and
ultimately unnecessary for conceptual data modeling. Prematurely
clustering attributes into entity records gets the data modeler into
trouble. Too much clustering can produce a data model with storage
redundancies and processing anomalies. Normalization is the test which
helps to identify the problems stemming from incorrect clustering, and
record decomposition is always the remedy to correct a violation of one
of the normal forms. Unfortunately, normalization is based upon
semantics which are not explicitly represented in ER diagrams.
This talk describes some problems that arise with a data modeling
scheme, such as ER Diagrams, which uses three basic constructs
(entity, attribute, relationship) and implicitly or explicitly clusters
attributes into entity records. Hopefully such a discussion will
motivate you to explore and seriously consider using a data modeling
scheme with two basic constructs, such as Object-Role Modeling (ORM).
About:
Dr. Gordon C. Everest is Professor Emeritus of
MIS and Data Management in the Carlson School of Management at the
University of Minnesota (but continues to teach as an adjunct at Univ.
of Minnesota, Metropolitan State University, and others). His Ph.D.
dissertation from the University of Pennsylvania Wharton School entitled
"Managing Corporate Data Resources" became the textbook entitled:
"Database Management: Objectives, System Functions, and Administration"
(McGraw-Hill, 1986, and remained in print until 2002!). He is also a
contributing author of the CODASYL Systems Committee technical report
entitled: "A Framework for Distributed Database Systems: Distribution
Alternatives and Generic Architectures", and of the final technical
report of the ANSI ASC X3 SPARC DBSSG Object-Oriented DBMS Task Group,
released in 1991. He participated in the ANSI standards community on
developing a Common Unified Data Modeling Scheme and investigating
Object-Oriented Database Management Systems.
Gordon has been teaching all about databases, database management
systems, database administration, and data warehousing since he joined
the University in 1970. Students learn the theory of databases, gain
practical experience with real data modeling projects, and with hands-on
use of data modeling tools and DBMSs. Besides teaching about databases,
he has helped many organizations and government agencies design their
databases. His approach transfers expertise to professional data
architects within those organizations by having them participate in and
observe the conduct of database design project meetings with the subject
matter experts.
