Introduction to Data Modelling (Information Modelling)
Data modelling has already been discussed in chapter 6 of structured analysis.
In the context or structured analysis data modelling can be used to represent the contents of data stores and the relationships that exist among them. Structured analysis notation provides no direct mechanism for representing this relationships. Data modelling does.
As such the concept of data modelling is same in object oriented approach. In data modelling we focus solely on data to define data objects, their attributes and their relationships with each other which leads to develop a data network of the given system. Data modelling is useful and beneficial for application like complex data base application in which data with their relationship are required to govern data.
Data modelling and some of its graphic notations are similar to those used for OOA. But there are many difference between these two approaches:
1. Both approaches use the term object. In data modelling it is referred as data object whereas in objects oriented approach it is simply an object. The definition of objects is much more limited in data modelling context in comparison to OO approach.
2. Both approaches describe relationship between objects but data modelling does not concern itself with how these relationship are achieved.
3. Data modelling basically models the data without concerning about the processing which transforms the data. So this approach should be associated with another modelling approach which will consider the processing issue to from a complete requirements analysis methods.
But in the OOA it does not happen. It is already an analysis method, to acquire the complete requirements.
These differences make their concepts more clear with respect to their use and applications. Now we will discuss data objects, their attributes and relationships and E-R diagrams one by one in the following sections.
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