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Conceptual data modeling is a technique for analyzing and describing the data needed by the users of a system. In analyzing the data, one must focus on understanding the conceptual structure of the data. The data description has to be readable by users, programmers, and other technical specialists,
because it is a blue print for data base design. Describing the data for a system is difficult.
Not only does a typical system have many
users who employ many different inputs and outputs, hut the analyst is usually not familiar with the system and must learn about it as he or she analyzes and describes the date. The description of data must he detailed, to satisfy the processing needs of the system. Yet the description must also he general so that it results in a database that satisfies the overall data needs of the organization. As if the task were not difficult enough already, the analyst must produce the data description within the time and budget constraints for the project.
A data model, on the other hand, encourages the analyst to base the analysis of data on the needs of the organization and on the way the users view or conceptualize, the data.
Because the data model describes data from the perspective of the organization not from the perspective of the detailed system processes - it leads to data base that is more adaptable to the data needs of the organization.
In this article, for the purpose of conceptual data modeling, a set of constructs (entity, relationship, attribute, identifier, and dependency) for defining data, rules controlling how the constructs are drawn to form a data model; and a method for constructing the data model using the
constructs and rules, have been defined.