Avoiding Pitfalls in Data Modeling - High-Performance Web Databases: Design, Development, and Deployment - page 274

Completeness
A data model goes beyond an entity-relationship diagram, because it
must encompass rigorous definition of data modeling objects-that is, enti-
ties, relationships, and attributes. Rigorous definition includes key
attributes, domain rules, integrity constraints, algorithms for derived
attributes, data type, and data format.
Accuracy
Finally, a data model has to be accurate in representing facts about busi-
ness rules. In addition, it should be presented in a way that is clear, con-
cise, smooth, and natural to allow users to verify it with ease.
Misrepresentation of facts could arise from a lack of understanding of
techniques or from a misunderstanding of users' requirements. It is there-
fore important to provide a data model that is semantically precise, that
uses the correct techniques, and is complete in its descriptions.
DATA MODELING
For the purpose of discussion, an arbitrarily selected data modeling
notation-the crow's foot notation, as adopted by some of the Computer-
Aided Software Engineering tools in the market today-is used. It should be
pointed out that the same principles generally apply to other notations as
well. Exhibit 1 depicts the convention of the syntax or notations used in
this article.
Entity Type
An entity type is a person, place, thing, concept, event, or organization
that has characteristics of interest to the enterprise. For the sake of brev-
ity, the terms entity, attribute, and relationship as used in this article refer
to entity type, attribute type, and relationship type.
Exhibit 18-1. Data modeling notation conventions.