Database Reference
In-Depth Information
Real-world
Information
Semantic
Data Model
Requirements
Definition
Object-based
Data Model
Relational
Data Model
OR
Entity-
Relationship
Model
Figure 9-1
Data model transformation in the flow.
cover the transformation of the entity-relationship data model to the relational data
model; the transformation principles are the same. You can easily derive them your-
selves. So our concentration is on the transformation of the object-based data
model. Nevertheless, while providing examples or listing data model components,
we will present notations and components from both object-based and entity-
relationship data models.
MODEL TRANSFORMATION APPROACH
Obviously, first you need to firm up your requirements definition before beginning
any data modeling. We discussed requirements-gathering methods and contents of
requirements definitions in great detail. Requirements definition drives the design
of the semantic data model. Figure 9-1 shows the transition from the requirements
definition phase. Note the flow from real-world information to the eventual phase
of physical design. Note the model transformation activity.
Merits
Why go through the process of creating a semantic model first and then transform-
ing it into a relational data model? Does it not sound like a longer route to logical
design? What are the merits and advantages of the approach? Although we have
addressed these questions earlier, in bits and pieces, let us summarize the merits and
rationale for the model transformation approach.
Need for Semantic Model
You must ensure that your final database system
stores and manages all aspects of the information requirements. Nothing must be
missing from the database system. Everything should be correct. The proposed data-
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