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Chapter 4 Entity Relationship (E-R) Modeling. Database Systems: Design, Implementation, and Management 4th Edition Peter Rob & Carlos Coronel. Basic Modeling Concepts. Database design is both art and science.
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Chapter 4Entity Relationship (E-R) Modeling Database Systems: Design, Implementation, and Management 4th Edition Peter Rob & Carlos Coronel
Basic Modeling Concepts • Database design is both art and science. • A data model is the relatively simple representation, usually graphic, of complex real-world data structures. It represents data structures and their characteristics, relations, constraints, and transformations. • The database designer usually employs data models as communications tools to facilitate the interaction among the designer, the applications programmer, and the end user. • A good database is the foundation for good applications.
Figure 4.1 Four Modified (ANSI/SPARC) Data Abstraction Models
Data Models: Degrees of Data Abstraction • The Conceptual Model • The conceptual model represents a global view of the data. It is an enterprise-wide representation of data as viewed by high-level managers. • Entity-Relationship (E-R) model is the most widely used conceptual model. • The conceptual model forms the basis for the conceptual schema. • The conceptual schema is the visual representation of the conceptual model. • The conceptual model is independent of both software (software independence) and hardware (hardware independence).
Tiny College Entities Figure 4.2
A Conceptual Schema for Tiny College Figure 4.3
Data Models: Degrees of Data Abstraction • The Internal Model • The internal model adapts the conceptual model to a specific DBMS. • The internal model is software-dependent. • Development of the internal model is especially important to hierarchical and network database models.
Data Models: Degrees of Data Abstraction • The External Model • The external model is the end user’s view of the data environment. • Each external model is then represented by its own external schema. CREATE VIEW CLASS_VIEW ASSELECT (CLASS_ID, CLASS_NAME, PROF_NAME, CLASS_TIME, ROOM_ID)FROM CLASS, PROFESSOR, ROOMWHERE CLASS.PROF_ID = PROFESSOR.PROF_ID AND CLASS.ROOM_ID = ROOM.ROOM_ID;
Figure 4.5 The External Models for Tiny College
Data Models: Degrees of Data Abstraction • The External Model • Advantages of Using External Schemas • It makes application program development much simpler. • It facilitates the designer’s task by making it easier to identify specific data required to support each business unit’s operations. • It makes the designer’s job easier by providing feedback about the conceptual model’s adequacy. • It helps to ensure security constraints in the database design.
Data Models: Degrees of Data Abstraction • The Physical Model • The physical model operates at the lowest level of abstraction, describing the way data is saved on storage media such as disks or tapes. • It requires the definition of both the physical storage devices and the access methods required to reach the data within those storage devices. • The physical model is both software and hardware-dependent. • It requires detailed knowledge of hardware and software used to implement the database design.
The Entity Relationship (E-R) Model • E-R model is commonly used to: • Translate different views of data among managers, users, and programmers to fit into a common framework. • Define data processing and constraint requirements to help us meet the different views. • Help implement the database.
The Entity Relationship (E-R) Model • E-R Model Components • Entities • In E-R models an entity refers to the entity set. • An entity is represented by a rectangle containing the entity’s name. • Attributes • Attributes are represented by ovals and are connected to the entity with a line. • Each oval contains the name of the attribute it represents. • Attributes have a domain -- the attribute’s set of possible values. • Attributes may share a domain. • Primary keys are underlined. • Relationships
The Attributes of the STUDENT Entity Figure 4.6
Basic E-R Model Entity Presentation Figure 4.7
The Entity Relationship (E-R) Model • Classes of Attributes • A simple attribute cannot be subdivided. • Examples: Age, Sex, and Marital status • A composite attribute can be further subdivided to yield additional attributes. • Examples: • ADDRESS Street, City, State, Zip • PHONE NUMBER Area code, Exchange number
The Entity Relationship (E-R) Model • Classes of Attributes • A single-valued attribute can have only a single value. • Examples: • A person can have only one social security number. • A manufactured part can have only one serial number. • Multivalued attributes can have many values. • Examples: • A person may have several college degrees. • A household may have several phones with different numbers • Multivalued attributes are shown by a double line connecting to the entity.
The Entity Relationship (E-R) Model • Multivalued Attribute in Relational DBMS • The relational DBMS cannot implement multivalued attributes. • Possible courses of action for the designer • Within the original entity, create several new attributes, one for each of the original multivalued attribute’s components (Figure 4.9). • Create a new entity composed of the original multivalued attribute’s components (Figure 4.10). Table 4.1
Splitting the Multivalued Attributes into New Attributes Figure 4.9
A New Entity Set Composed of Multivalued Attribute’s Components Figure 4.10
The Entity Relationship (E-R) Model • A derived attribute is not physically stored within the database; instead, it is derived by using an algorithm. • Example: AGE can be derived from the data of birth and the current date. Figure 4.11 A Derived Attribute
The Entity Relationship (E-R) Model • Relationships • A relationship is an association between entities. • Relationships are represented by diamond-shaped symbols. Figure 4.12 An Entity Relationship
The Entity Relationship (E-R) Model • A relationship’s degree indicates the number of associated entities or participants. • A unary relationship exists when an association is maintained within a single entity. • A binary relationship exists when two entities are associated. • A ternary relationship exists when three entities are associated.
The Implementation of a Ternary Relationship Figure 4.14
The Entity Relationship (E-R) Model • Connectivity • The term connectivity is used to describe the relationship classification (e.g., one-to-one, one-to-many, and many-to-many). Figure 4.15 Connectivity in an ERD
The Entity Relationship (E-R) Model • Cardinality • Cardinality expresses the specific number of entity occurrences associated with one occurrence of the related entity. Figure 4.16 Cardinality in an ERD
Existence Dependency • If an entity’s existence depends on the existence of one or more other entities, it is said to be existence-dependent. Figure 4.18
The Entity Relationship (E-R) Model • Relationship Participation • The participation is optional if one entity occurrence does not require a corresponding entity occurrence in a particular relationship. • An optional entity is shown by a small circle on the side of the optional entity. Figure 4.19 An ERD With An Optional Entity
Figure 4.20 CLASS is Optional to COURSE Figure 4.21 COURSE and CLASS in a Mandatory Relationship
The Entity Relationship (E-R) Model • Weak Entities • A weak entity is an entity that • Is existence-dependent and • Has a primary key that is partially or totally derived from the parent entity in the relationship. • The existence of a weak entity is indicated by a double rectangle. (Figure 4.22) • The weak entity inherits all or part of its primary key from its strong counterpart.
A Weak Entity in an ERD Figure 4.22
An Illustration of the Weak Relationship Between DEPENDENT and EMPLOYEE Figure 4.23
The Entity Relationship (E-R) Model • Recursive Entities • A recursive entity is one in which a relationship can exist between occurrences of the same entity set. • A recursive entity is found within a unary relationship. Figure 4.24 An E-R Representation of Recursive Relationships
Figure 4.25 Figure 4.26
The Implementation of the M:N Recursive “PART Contains PART” Relationship Figure 4.27
Implementation of the M:N “COURSE Requires COURSE” Recursive Relationship Figure 4.28
Implementation of the 1:M “EMPLOYEE Manages EMPLOYEE” Recursive Relationship Figure 4.29
The Entity Relationship (E-R) Model • Composite Entities • A composite entity is composed of the primary keys of each of the entities to be connected. • The composite entity serves as a bridge between the related entities. • The composite entity may contain additional attributes.
Converting the M:N Relationship Into Two 1:M Relationships Figure 4.30
The M:N Relationship Between STUDENT and CLASS Figure 4.31
A Composite Entity in the ERD Figure 4.32
The Entity Relationship (E-R) Model • Entity Supertypes and Subtypes Figure 4.33 Nulls Created by Unique Attributes
The Entity Relationship (E-R) Model • Entity Supertypes and Subtypes • The generalization hierarchy depicts the parent-child relationship. • The supertype contains the shared attributes, while the subtype contains the unique attributes. • A subtype entity inherits its attributes and its relationships from the supertype entity.
A Generalization Hierarchy Figure 4.34
The Entity Relationship (E-R) Model • Entity Supertypes and Subtypes • The supertype entity set is usually related to several unique and disjointed (nonoverlapping) subtype entity sets. • The supertype and its subtype(s) maintain a 1:1 relationship.
The EMPLOYEE/PILOT Supertype/Subtype Relationship Figure 4.35
The Entity Relationship (E-R) Model • Entity Supertypes and Subtypes • The generalization hierarchy depicts the parent-child relationship. (Figure 4.34) • The supertype contains the shared attributes, while the subtype contains the unique attributes. • The supertype entity set is usually related to several unique and disjointed (nonoverlapping) subtype entity sets. • The supertype and its subtype(s) maintain a 1:1 relationship.