Data model
In practice, a data model can be very simple and small, but also very comprehensive and detailed. The main scope and detail factors are the scope and complexity of the application area, the quantity, diversity and growth rate of the data, existing data models at the professional and technical level, as well as the using divisions and stakeholders.
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Another added value of the model is the precise scoping. A data model maps parts of the scope, omitting or summarising aspects. Use the data model to determine which elements, features and connections of the real or virtual world need to be considered and which are not in scope. Shorten and abstract.
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Finally, the data model assumes a validation function for you. You use it to view a domain or technical domain from a structural point of view. Both current and future states can be checked. The focus is on the data, not the functions, capabilities, processes or behaviours.