Database Reference
In-Depth Information
tables. You have to look at the information requirements and arrive at the initial
set of tables mostly through intuition. You just start with the best possible set that
is complete. Then you proceed to normalize the tables and complete the relational
data model.
Other method systematic.
The method of creating the semantic data model
first and then transforming it into the required relational data model is a system-
atic method with well-defined steps. The semantic data model is created
through clearly defined data modeling techniques. You then take the components
of the semantic data model, one by one, and transform these in a disciplined
manner.
Choosing between the two methods.
When can you adopt the traditional method?
Only when you can come up with a good initial set of tables through intuition. If
the information requirements are wide and complex, by looking at the information
requirements it is not easy to discern the tables for the initial set. If you attempt
the process, you are likely to miss portions of information requirements. Therefore,
adopt the traditional approach only for smaller and simpler relational database
systems. For larger and more complex relational database systems, the transforma-
tion method is the prudent approach. As data modelers gain experience, they tend
to get better at defining the initial set of tables and choose the normalization
method.
CHAPTER SUMMARY
•
The relational data model is found to be superior to other earlier conventional
data models such as the hierarchical and network data models.
•
The relational data model, standing on solid mathematical principles, is a dis-
ciplined method for data organization, provides a simple and familiar view of
data in the form of tables, and, above all, links related data elements logically
and not physically.
•
A relation or a two-dimensional table with rows and columns is the single
modeling concept for this data model. The columns represent the attributes of
the entity; the rows represent single instances of the entities.
•
Relationships between tables or relations are established through foreign keys,
not physical pointers.
•
To provide data integrity and consistency, the set of tables in a relational model
must conform to relational constraints or rules. The entity integrity rule governs
the integrity of a single relation; the referential integrity rule stipulates condi-
tions for two related tables.
•
Each data item in a row or tuple of a relation must depend on the entire
primary key alone, not on any other attribute in the row.
•
Relational algebra and relational calculus are two generic languages for data
manipulation in a relational data model. Relational algebra is a procedural lan-
guage consisting of distinct operations; relational calculus, being a nonpro-
cedural language, just specifies the solution in the form of single statements.
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