Entity names are red attributes are blue. In the CASE tool used for examples in this chapter, entities are organized alphabetically, with the attributes following the entity name.
The layout of a data dictionary varies with the specific CASE tool, as does the way in which entries are configured. In addition, by linking entries in the ER diagram to the data dictionary you can provide enough information for the CASE tool to generate the SQL CREATE statements needed to define the structure of the database. Since you were introduced to several types of ER diagrams in Chapter 4, we will not repeat them here, but instead focus on the interaction of the diagrams and the data dictionary.Ī data dictionary provides a central repository for documenting entities, attributes, and domains.
Harrington, in Relational Database Design and Implementation (Fourth Edition), 2016 The Data Dictionaryįrom a database designer’s point of view, the ER diagram and its associated data dictionary are the two most important parts of CASE software. In the above example, the relation between College and Course is acting as an Entity in Relation with Student.Jan L.
It is a process when two entity is treated as a single entity. It abstracts a relationship between objects and viewing the relationship as an object. Aggregation is a process that represent a relationship between a whole object and its component parts. A Category member must exist in at least one of its super classes. Category (sub class) → Owner is a subset of the union of the three super classes → Company, Bank, and Person. It can be a total or partial participation.įor example Car booking, Car owner can be a person, a bank (holds a possession on a Car) or a company. Category represents a single super class or sub class relationship with more than one super class. In the above example, Employee can be specialized as Developer or Tester, based on what role they play in an Organization. It defines one or more sub class for the super class and also forms the superclass/subclass relationship. It maximizes the difference between the members of an entity by identifying the unique characteristic or attributes of each member. It is a top down approach, in which one higher entity can be broken down into two lower level entity. Specialization is a process that defines a group entities which is divided into sub groups based on their characteristic. In the above example, Tiger, Lion, Elephant can all be generalized as Animals. It minimizes the difference between the entities by identifying the common features. It defines a general entity type from a set of specialized entity type. Generalization is the reverse process of Specialization. It is a bottom approach, in which two lower level entities combine to form a higher level entity. Generalization is the process of generalizing the entities which contain the properties of all the generalized entities. Sub class inherits properties and attributes from its super class.įor example: Square, Circle, Triangle are the sub class of Shape super class. Sub class is a group of entities with unique attributes. An entity cannot exist in database merely by being member of any super class.įor example: Shape super class is having sub groups as Square, Circle, Triangle. Super class is an entity type that has a relationship with one or more subtypes. The relationship between sub class and super class is denoted with symbol. Sub class and Super class relationship leads the concept of Inheritance. It is used to represent a collection of objects that is union of objects of different of different entity types. It includes the concept of specialization and generalization. Diagrammatic technique helps for displaying the EER schema. 
It includes all modeling concepts of the ER model.It reflects the data properties and constraints more precisely.EER creates a design more accurate to database schemas.These concepts are used when the comes in EER schema and the resulting schema diagrams called as EER Diagrams. It is a diagrammatic technique for displaying the following concepts EER ModelEER is a high-level data model that incorporates the extensions to the original ER model.
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