DATA NORMALIZATION METHOD - Database Design and Development: An Essential Guide for IT Professionals - page 318

EMPLOYEE (EmpID, EmpName)

TRAINING (EmpID, SkillType, TrainerID)

Foreign Keys: TrainerID REFERENCES INSTRUCTOR

EmpID REFERENCES EMPLOYEE

INSTRUCTOR (TrainerID, TrainerName, Location, SubjectArea)

Foreign Key: SubjectArea REFERENCES TRAINING

Figure 10-13 Data model in domain-key normal form.

ditions under which one method is preferable to the other. You notice that both
methods finally produce a true and correct relational data model. In the final rela-
tional data model, every single relation or table represents just one object set or
entity type. In each relation, every attribute is functionally dependent on the full
primary key and only on the full primary key.
As you know, the data model transformation method is a more straightforward
approach. Systematically, you create partial semantic data models by applying stan-
dard techniques. You then integrate all the partial data models to produce the con-
solidated semantic model. After this step, you transform the consolidated semantic
model into a final relational data model. Although straightforward, the data model
transformation method might take longer to come up with the final relational data
model.
On the other hand, the normalization approach starts out with an intuitive initial
data model. If you cannot begin with an intuitive initial data model that reflects the
real-world information requirements completely, then this method will not work.
That is why this normalization approach is difficult when the real-world informa-
tion requirements are large and complex. If you are able to start with a good initial
data model, then it is a matter of rendering the initial data model into a successive
series of normal forms. Each step brings you closer to the true relational data model.
Observe, however, that each step in the normalization process is defined well. In
each step, you know exactly the type of problem you have look for and correct. For
example, to refine the data model and make it a first normal form data model, you
remove repeating groups of attributes. To refine the data model and make it a
second normal data model, you look for partial key dependencies and rectify this
problem.

Review of the Steps

When we discussed the normalization steps, we grouped the steps into two major
sets. The first set of steps deal with the refinement of the data model into the fun-
damental normal forms. The second set of steps relate to higher normal forms. As
mentioned above, if you complete the first set of steps, then for a vast majority of
cases your resulting data model will be truly relational. You need not proceed to
the second set of steps to produce higher normal forms.