Entity Relationship (E-R) Modeling - PowerPoint PPT Presentation

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Entity Relationship (E-R) Modeling

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Title: Database systems design Author: Isabelle Bichindaritz Last modified by: ibichind Created Date: 9/29/2000 12:33:17 AM Document presentation format – PowerPoint PPT presentation

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Title: Entity Relationship (E-R) Modeling


1
Entity Relationship (E-R) Modeling
2
Learning Objectives
  • Conceptual model(s)
  • Internal and external models
  • Definition and refinement of relationships
    between entities during the database design
    process
  • ERD components and database design and
    implementation
  • Interpretation of the modeling symbols for the
    four most popular E-R modeling tools

3
Basic Modeling Concepts
  • Art and science
  • Good judgment coupled with powerful design tools
  • Models
  • Description or analogy used to visualize
    something that cannot be directly observed
    Websters Dictionary
  • A model is a representation of the world in
    simplified terms, it is an abstraction of the
    real world
  • Data Model
  • Relatively simple representation of complex
    real-world data structures

4
Data Models Degrees of Data Abstraction
Figure 3.1
5
Degrees of Abstraction
  • Conceptual
  • Global view of data from application domain,
    based on end-users requirements
  • Basis for identification and description of main
    data items
  • ERD used to graphically represent conceptual data
    model (or class diagram in UML)
  • Hardware and software (and DBMS) independent
  • Internal
  • Representation of database as seen by DBMS
  • Adapts conceptual model to a specific DBMS
  • Software dependent

6
Degrees of Abstraction
  • External
  • Users views of data environment
  • Provides subsets of internal view
  • Makes application program development easier
  • Facilitates designers tasks
  • Ensures adequacy of conceptual model
  • Ensures security constraints in design
  • Physical
  • Lowest level of abstraction
  • Software and hardware dependent
  • Requires definition of physical storage devices
    and access methods

7
Degrees of Abstraction
  • Three main levels of data models deliverables
  • Conceptual data model
  • Project initiation and planning ERDs with
    entities and relationships only
  • Analysis ERDs refined with attributes
  • Logical data model Internal external data
    model a set of normalized relations, based on
    ERD and views/forms design
  • Physical data model physical file and database
    design

8
Conceptual Data Model Example
9
Internal / External Data Models Example
10
The Entity Relationship (E-R) Model
  • Represents conceptual view
  • Main Components
  • Entities
  • Stands for entity set
  • Corresponds to entire table, not row
  • Represented by rectangle
  • Rows correspond to entity instances or entity
    occurrences
  • Attributes
  • Represented by ovals or in entity
  • Relationships
  • Represented by diamonds or just a relationship
    name

11
Attributes
  • Characteristics of entities
  • Domain is set of possible values ( (true, false),
    )
  • Primary keys underlined

12
Attributes
  • Simple
  • Cannot be subdivided
  • Age, sex, marital status
  • Composite
  • Can be subdivided into additional attributes
  • Address into street, city, zip
  • Single-valued
  • Can have only a single value
  • Person has one social security number
  • Multi-valued
  • Can have many values
  • Person may have several college degrees
  • Can be represented by a 1-M relationship
  • Derived
  • Can be derived with algorithm
  • Age can be derived from date of birth

13
Attributes
  • ExamplesCLASS(CLASS_CODE, CRS_CODE,
    CLASS_SECTION, CLASS_TIME, CLASS_ROOM,
    PROF_NUM)CLASS(CRS_CODE, CLASS_SECTION,
    CLASS_TIME, CLASS_ROOM, PROF_NUM)STUDENT(Student
    _Id, Student_Name, Address, Phone_Number, Major)

14
Multivalued Attributes
15
Multivalued Attributes
16
Derived Attributes
17
Relationships
  • Association between entities
  • Connected entities are called participants
  • Operate in both directions
  • Connectivity describes relationship
    classification
  • 11, 1M, MN
  • Cardinality
  • Expresses number of entity occurrences associated
    with one occurrence of related entity (1,4),
    (1,N),
  • How many classes does a professor teach ? (1,4)

18
Connectivity and Cardinality in an ERD
Figure 3.12
19
Relationship Strength
  • Existence dependence
  • Entitys existence depends on existence of
    related entities
  • Existence-independent entities can exist apart
    from related entities
  • EMPLOYEE claims DEPENDENT
  • Weak (non-identifying)
  • One entity is existence-independent on another
  • PK of related entity doesnt contain PK component
    of parent entity
  • Strong (identifying)
  • One entity is existence-dependent on another
  • PK of related entity contains PK component of
    parent entity

20
Weak Relationship
IE Inversion Entity a non-unique identifier
for an entity
21
Strong Relationship
22
Relationship Participation
  • Optional
  • Entity occurrence does not require a
    corresponding occurrence in related entity
  • Shown by drawing a small circle on side of
    optional entity on ERD
  • Mandatory
  • Entity occurrence requires corresponding
    occurrence in related entity
  • If no optionality symbol is shown on ERD, it is
    mandatory

23
Optional Participation
24
Weak Entity
  • Existence-dependent on another entity
  • Has primary key that is partially or totally
  • derived from parent entity

Figure 3.19
25
Relationship Degree
  • Indicates number of associated entities
  • Unary
  • Single entity
  • Recursive
  • Exists between occurrences of same entity set
  • Binary
  • Two entities associated
  • Ternary
  • Three entities associated

26
Three Types of Relationships
Figure 3.21
27
Composite Entities
  • Used to bridge between MN relationships
  • Bridge entities composed of primary keys of each
    entity needing connection

Figure 3.30
28
Composite Entities (cont.)
Figure 3.31
29
Composite Entities (cont.)
30
Entity Supertypes and Subtypes
  • Generalization hierarchy
  • Depicts relationships between higher-level
    supertype and lower-level subtype entities
  • Supertype has shared attributes
  • Subtypes have unique attributes
  • Disjoint relationships
  • Unique subtypes
  • Non-overlapping
  • Indicated with a G
  • Overlapping subtypes use Gs Symbol

31
Generalization Hierarchy with Disjoint Subtypes
32
Generalization Hierarchy with Overlapping Subtypes
Figure 3.35
33
Comparison of E-R Modeling Symbols
  • Alternate styles developed to enable easier use
    of CASE tools
  • Chen
  • Moved conceptual design into practical database
    design arena
  • Crows Foot
  • Cannot detail all cardinalities
  • Rein85
  • Similar to Crows Foot
  • Operates at higher level of abstraction
  • IDEF1X
  • Derivative of ICAM studies in the late 1970s
  • Uses fewer symbols

34
Comparison of E-R Modeling Symbols
Figure 3.36
35
Developing an E-R Diagram
  • Iterative Process
  • Step1 General narrative of organizational
    operations developed
  • Step2 Basic E-R Model graphically depicted and
    reviewed
  • Step3 Modifications made to incorporate newly
    discovered E-R components
  • Repeat process until designers and users agree
    E-R Diagram complete

36
Supertype/Subtype Relationship in an ERD
Figure 3.42
37
First ERD Segment Established
Figure 3.43
38
Second and Third ERD Segments Established
Figures 3.44 3.45
39
Fourth and Fifth ERD Segments Established
Figures 3.46 3.47
40
Sixth and Seventh ERD Segments Established
Figures 3.48 3.49
41
Eighth ERD Segment Established
Figures 3.50
42
Ninth ERD Segment Established
Figures 3.51
43
Components of E-R Model
Table 3.2
44
Completed ERD
Figure 3.52
45
Challenge of Database Design Conflicting Goals
  • Database must be designed to conform to design
    standards
  • High-speed processing may require design
    compromises
  • Quest for timely information may be the focus of
    database design
  • Other concerns
  • Security
  • Performance
  • Shared access
  • Integrity

46
Burger Inventory Example
  • The Burger store wants to develop a new inventory
    system. Analysts have determined that the
    following data are required to represent the data
    needed by the inventory system
  • An INVOICE includes one or more INVOICE ITEMS,
    each of which corresponds to an INVENTORY ITEM.
    Obviously, an INVOICE ITEM cannot exist without
    an associated INVOICE, and over time, there will
    be zero to many receipts, or INVOICE ITEMs, for
    an INVENTORY SYSTEM.

47
Burger Inventory Example
  • Each PRODUCT has a RECIPE of INVENTORY ITEMs,
    containing several RECIPE LINEs. Thus, RECIPE
    LINE is an associative entity supporting a
    bill-of-materials type relationship between
    PRODUCT and INVENTORY ITEM.
  • A SALE indicates that Burger sells one or more
    ITEM SALES, each of which corresponds to a
    PRODUCT. ITEM SALE cannot exist without an
    associated SALE, and over time there will be zero
    to many ITEM SALES for a PRODUCT.
  • Note the following ERD does not represent weak
  • entities,and relationships. Do you see any ?

48
Burger Inventory Example
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