Data Modeling with the Entity-Relationship Model - Database Processing: Fundamentals, Design, and Implementation - page 180

process using the example of a small database at a university. Before starting,
however, you need to understand the purpose of a data model.
Data modeling occurs in the requirements analysis step of the systems
development life cycle (SDLC) in the systems analysis and design process.
For an introduction to systems analysis and design, and to the SDLC, see
Appendix B.

The Purpose of a Data Model

A data model is a plan, or blueprint, for a database design—it is a generalized, non-DBMS
specific design. By analogy, consider the construction of your dorm or apartment building. The
contractor did not just buy some lumber, call for the concrete trucks, and start work. Instead,
an architect constructed plans and blueprints for that building long before construction be-
gan. If, during the planning stage, it was determined that a room was too small or too large,
the blueprint could be changed simply by redrawing the lines. If, however, the need for change
occurs after the building is constructed, the walls, electrical system, plumbing, and so on will
need to be rebuilt, at great expense and loss of time. It is easier, simpler, and faster to change
the plan than it is to change a constructed building.
The same argument applies to data models and databases. Changing a relationship during
the data modeling stage is just a matter of changing the diagram and related documentation.
Changing a relationship after the database and applications have been constructed, however, is
much more difficult. Data must be migrated to the new structure, SQL statements will need to
be changed, forms and reports will need to be altered, and so forth.

Topics on systems analysis and design often identify three design stages:

By ThE Way

● Conceptual design (conceptual schema)

● Logical design (logical schema)

● Physical design (physical schema)

The data model we are discussing is equivalent to the conceptual design as defined in
these topics.

The Entity-Relationship Model

Dozens of different tools and techniques for constructing data models have been defined over
the years. They include the hierarchical data model, the network data model, the ANSI/SPARC
data model, the entity-relationship data model, the semantic object model, and many others.
Of these, the entity-relationship data model has emerged as the standard data model, and we
will consider only that data model in this chapter.
The entity-relationship data model is commonly know as the entity-relationship (E-R)
model , and was first described in a paper published by Peter Chen in 1976. 1 In this paper, Chen
set out the basic elements of the model. Subtypes (discussed later) were added to the E-R model
to create the extended E-R model , 2 and today it is the extended E-R model that most people
mean when they use the term E-R model . In this text, we will use the extended E-R model.

1 Peter P. Chen, “The Entity-Relationship Model—Towards a Unified View of Data,” ACM Transactions on
Database Systems , January 1976, pp. 9-36. For information on Peter Chen, see http://en.wikipedia.org/wiki/
Peter_Chen , and for a copy of the article, see http://csc.lsu.edu/news/erd.pdf .
2 T. J. Teorey, D. Yang, and J. P. Fry, “A Logical Design Methodology for Relational Databases Using the Extended
Entity-Relationship Model,” ACM Computing Surveys , June 1986, pp. 197-222.