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Notes > Database Systems > Logical and Conceptual Data Models

The purpose of Data Modelling is to aid the understanding of the data and its semantics (meaning). Different users will have different perspectives of the data, and so, these perspectives need to be designed and understood. Data modelling allows independent analysis of the data, irrespective of how it is physically stored and represented. Because of this distancing of the data model from the physical storage system, data models can be applied to any platform. Building data models based on a common syntax that is widely understood means that the data model and design can be understood by many more individuals than just the designer.

Logical Data Model

Logical database design has the aim of creating a data model that is completely independent from any particular DBMS or software/hardware platform. A conceptual model is typically needed before the logical model is constructed. If the system is a particularly large one, it is often the case that individual logical models are constructed for each user view or area within the business. These separate models are then merged into a global logical data model.

An example logical data model of a simple library system is shown below:

Logical Model

Conceptual Data Model

The conceptual model purely documents the data and information within the business and how it is used. The logical model is different from the conceptual model in that it takes into consideration the relational or object-oriented theory which will be used to store the data. In some cases, the conceptual data model may be the same as the logical data model.

An example conceptual model is shown below. It is based on the same system as modelled in the logical data model above. Note that extra entities / relations have been added to enable the information and relationships to be stored in a relational database.

Conceptual Model

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