The information is structured using data models and data model hierarchies (nesting of data models).
A data model is made up of entity types, relationship categories and specialization categories. Semantically related objects are combined to form their own data model. Complex models are split into smaller submodels which can themselves also be structured.
There are some special types of data model:
A model is termed an application data model if it forms an independent unit from a commercial viewpoint. Examples of application data models are SAP's FI and MM models.
A business object is a set of entity types sharing a common external interface. A business object normally consists of a source entity type and all those entity types hierarchically dependent on it. The source entity type normally functions as representative of the business object to which it belongs.
The entity types Warehouse and Storage bin could be regarded as a business object. In this case, the entity type Storage bin is hierarchically dependent on the entity type Warehouse, which is the source entity type.
A data model can have the following references:
The representative of a data model is the entity type that represents the entity types belonging to the data model when the model is compressed.
The referenced model is the data model on which the current data model is based. A data model is normally derived from the referenced data model by means of projection.
A future version of the Data Modeler will allow you to compare the two models and to display the differences between them.
Data model hierarchy
The underlying structure of a data model is termed the data model hierarchy. It takes the form of an oriented acyclic graph. Data models and entity types can be used in several data models.
For example, the entity type Plant is used both in the FI data model and the MM data model.
The data model hierarchy provides you with a fast method of obtaining an overview of the structure of a data model and the entity types and submodels participating in it.