Database Reference
In-Depth Information
network, and relational data models are conventional data models. These dictate
the view and arrangement of data in the database. A conventional data model is
based on a set of standards or conventions developed in a certain way and accepted.
The hierarchical model views data in a database as arranged in a hierarchical, top-
down fashion; the network model views as arranged in a network configuration.
On one side, the semantic data model—a generic data model—represents the
information requirements of an organization. On the other side, the conventional
data model represents how data stored in the database are perceived. Each of the
three conventional data models has its own way of perceiving the arrangement of
data. Now, if your organization wants to implement a hierarchical database, you take
your semantic data model and transform it into a conventional, hierarchical model
and implement the hierarchical database. You take similar routes from the seman-
tic data model to the implementation of your database if your organization wants
to have a network database or a relational database. The big advantage of creating
a semantic data model first is this—being generic, the semantic data model can be
transformed into any type of conventional data model.
STRUCTURE AND COMPONENTS
The relational model uses familiar concepts to represent data. In this model, data
are perceived as organized in traditional, two-dimensional tables with columns and
rows. The rigor of mathematics is incorporated into the formulation of the model.
It has its theoretical basis in mathematical set theory and first-order predicate logic.
The concept of a relation comes from mathematics and represents a simple two-
dimensional table.
The relational model derives its strength from its simplicity and the mathemati-
cal foundation on which it is built. Rows of a relation are treated as elements of a
set. Therefore, manipulation of rows may be based on mathematical set operations.
Dr. Codd used this principle and provided with two generic languages for manipu-
lating data organized as a relational model.
A relation or two-dimensional table forms the basic structure in the relational
model. What are the implications? In requirements gathering, you collect so much
information about business objects or entities, their attributes, and relationships
among them. All of these various pieces of information can be represented in the
form of relations. The entities, their attributes, and even their relationships are all
contained in the concept of relations. This provides enormous simplicity and makes
the relational model a superior conventional data model.
Strengths of the Relational Model
Before we proceed to explore the relational model in detail, let us begin with a list
of its major strengths. This will enable you to appreciate the superiority of the model
and help you understand its features in a better light. Here is a summary of the
strengths:
Mathematical relation.
Uses the concept of a mathematical relation or two-dimen-
sional table to organize data. Rests on solid mathematical foundation.
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