Data models play a key role in bringing together all segments of an enterprise – IT, business analysts, management and others – to cooperatively design information systems (and the databases they rely on).
These systems require properly defined and formatted data, and models shine a clear light on what data is required and how it must be structured to support the desired business processes.
By explicitly determining the structure of your data, these models support a variety of use cases, including database modeling, information system design, and process development in support of a consistent, clean exchange of data.
It’s also important to understand the three different types of data models. Each will serve a different purpose as you work through the data modeling process.
Ultimately, all three models can and should work independently of each other. But as your project matures, the best results will come from a natural progression through all three models. Of course, consistency must be maintained across the models on a structural level. Adjusting the table/column format on a physical model, for example, should not change the initial conceptual model in any meaningful way.
By leveraging all three models, organizations can ensure their projects do not lose sight of initial objectives – but still maintain the flexibility to address unexpected changes in requirements or parameters.