Data modeling: Difference between revisions

Revision as of 11:16, 23 February 2023

Revision as of 00:32, 14 March 2023

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{{Short description|Creating a model of the data in a system}}

{{For|data-model abstraction|data model}}

{{duplicatesduplication|dupe=Data model|date=March 2023}}

{{Use mdy dates|date=March 2016}}

[[File:4-3 Data Modelling Today.svg|420px|thumb|The data modeling process. The figure illustrates the way data models are developed and used today . A [[Conceptual schema|conceptual data model]] is developed based on the data [[requirement]]s for the application that is being developed, perhaps in the context of an [[activity diagram|activity model]]. The data model will normally consist of entity types, attributes, relationships, integrity rules, and the definitions of those objects. This is then used as the start point for interface or database design.<ref name="MW99"/>]]

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* Business rules, specific to how things are done in a particular place, are often fixed in the structure of a data model. This means that small changes in the way business is conducted lead to large changes in computer systems and interfaces. So, business rules need to be implemented in a flexible way that does not result in complicated dependencies, rather the data model should be flexible enough so that changes in the business can be implemented within the data model in a relatively quick and efficient way.

* Entity types are often not identified, or are identified incorrectly. This can lead to replication of data, data structure and functionality, together with the attendant costs of that duplication in development and maintenance. Therefore, data definitions should be made as explicit and easy to understand as possible to minimize misinterpretation and duplication.

* Data models for different systems are arbitrarily different. The result of this is that complex interfaces are required between systems that share data. These interfaces can account for between 25- and 70% of the cost of current systems. Required interfaces should be considered inherently while designing a data model, as a data model on its own would not be usable without interfaces within different systems.

* Data cannot be shared electronically with customers and suppliers, because the structure and meaning of data has not been standardised. To obtain optimal value from an implemented data model, it is very important to define standards that will ensure that data models will both meet business needs and be consistent.<ref name="MW99"/>