There are three types of data models – physical, conceptual, and logical. Conceptual data models are representations of general characteristics of a specific system. These models analyze how different types of data are related to each other. Logical data models are detailed representations of data, which are more specific when compared to conceptual data models. Whereas conceptual models focus on overall characteristics, logical models showcase specific features of separate data structures in the system. Physical data models are representations of the ways a physical system should be implemented in the form of blueprints. The most common specific types are textual and graphical data models.
The first step in selection a data model is to ascertain the objective of a project. Depending on the level of the project’s complexity, the choice between a conceptual and logical data model is made. The second step is to understand the importance of details – the more important they are, the more reasons to use the logical data model there are. The third step is to ascertain the necessity for the physical system. If it is established, the physical data model will be chosen. The fourth step is to understand the most effective means of presenting data. If the audience is more interested in primary data, textual data models will be used. If it is only necessary to showcase relationships, graphical models are the most appropriate.
Data modelling allows the developer to understand the complexity of data structures. The more sophisticated the system is, the more detailed type of data model will be used. the more functional requirements it will need to perform. Similarly, using data modelling will also determine the sophistication of functional requirements (Tenório et al., 2017). For instance, if the developer identifies the need for a logical data model, they will also conclude that the number of functional requirements will depend on the number of logical requirements of the system.
References
Tenório, N., Pinto, D., Vidotti, A. F., de Oliveira, M. S., Urbano, G. C., & Bortolozzi, F. (2017). Tool based on knowledge management process: An interview protocol to gather functional requirements from software industry experts.MATTER: International Journal of Science and Technology, 3(1), 45-54.