Database Reference
In-Depth Information
In practice, only a few initial data models need to go through all the above steps.
Generally, a set of third normal form relations will form a good relational data
model. You may want to go one step further to make the model a set of Boyce-
Codd normal form relations. Only very infrequently would you need to go to higher
normal forms.
FUNDAMENTAL NORMAL FORMS
As explained above, normalization is a process of rectifying potential problems in
two-dimensional tables created at random. This process is a step-by-step method,
each step addressing and remedying one specific type of potential problem. As we
proceed with the normalization process, you will clearly understand why this step-
by-step approach works so well. By taking a step-by-step approach, you will not
overlook any type of anomaly. And, when the process is completed, you will have
resolved every type of potential problem.
In the last section, we have noted the four steps that make up the portion of the
normalization process transforming the initial data model into the fundamental
normal forms. After the third step, the initial data model becomes a third
normal form relational data model. As already mentioned, for most practical pur-
poses, a third normal form data model is an adequate relational data model. You
need not go further. Occasionally, you may have to proceed to the fourth step
and refine the data model further and make it a set of Boyce-Codd normal form
relations.
First Normal Form
Refer back to Figure 10-2 showing the PROJECT-ASSIGNMENT relation created
as the initial data model. You have already observed that the rows for Davis, Berger,
Covino, Smith, and Rogers contain multiple values for attributes in six different
columns. You know that this violates the requirement in a relational model that
states each row must have atomic values for each of the attributes.
This step in normalization process addresses the problem of repeating groups of
attribute values for single rows. If a relation has such repeating groups, we say that
the relation is not in the first normal form. The objective of this step is to transform
the data model into a model in the first normal form. Here is what must be done
to make this transformation.
Transformation to First Normal Form (1NF)
Remove repeating groups of attributes and create rows without repeating groups.
Figure 10-3 shows the result of the transformation to first normal form.
Carefully inspect the PROJECT-ASSIGNMENT relation shown in the figure.
Each row has a set of unique values in the columns. The composite primary key
consisting of EmpId and ProjNo uniquely identifies each row. No single row has
multiple values for any of its attributes. This step has rectified the problem of mul-
tiple values for the same attribute in a single row.
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