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Entity-Relation Modeling Hun Myoung Park, Ph.D., Public Management and Policy Analysis Program Graduate School of International Relations International.

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Presentation on theme: "Entity-Relation Modeling Hun Myoung Park, Ph.D., Public Management and Policy Analysis Program Graduate School of International Relations International."— Presentation transcript:

1 Entity-Relation Modeling Hun Myoung Park, Ph.D., Public Management and Policy Analysis Program Graduate School of International Relations International University of Japan

2 Outline  Business Rules  Entity-Relation Model  Entity of E-R Model  Attribute of E-R Model  Relationship of E-R Model  Degree of Relationship  Cardinality of a Relationship  CASE Tools 2

3 Business Rules  “A statement that defines or constrains some aspect of the business”  “Govern how data are handled and stored”  “Derived from policies, procedures, events, functions, and other business objects”  “Documenting rules and policies of an organization that govern data is exactly what data modeling is all about.” 3

4 Entity-Relationship Model  A database modeling method that produces “a detailed, logical representation of the data”  Produces a conceptual schema in a relational database  Introduced by Peter Chen in 1976  Represented by entity-relationship diagram (ERD) 4

5 Entity-Relationship Diagram  E-R diagram (ERD) represents the abstract and conceptual relationships in ERM.  Components of ERD  Entity with attributes  Relationship among entities  Cardinality 5

6 Entity of E-R Model 1  Represented by a rectangle or box in ERD  Name in uppercase  Name as singular noun form  Includes a set of attributes  Entity type versus entity instance 6

7 Entity of E-R Model 2  Entity type is “ a collection of entities that share common properties ”  Entity instance is “ a single occurrence of an entity type ”  Strong (unique/independent) entity type versus weak (dependent) entity type 7

8 Entity of E-R Model 3  Associative entity  Associate the instances of entity types  Contains attributes that are peculiar to the relationship among the entity instances.  Relationship in a rectangular with rounded corners or dashed line 8

9 Attribute of E-R Model 1  A property of an entity type  Singular none or none phrase  Sentence-cased  Required (must have values) in boldface v.s. optional attribute (may not) 9

10 Attribute of E-R Model 2  Simple (atomic) attribute v. s. composite attribute (having meaningful components parts such as last name and first name) in (…)  Single-valued v.s. multi-valued attribute in {…}  Stored v.s. derived attribute (e.g., age calculated from date of birth) in […] 10

11 Relationship of E-R Model 1  Connectivity (association) representing an interaction among instances of entity types  Relationship type is “a meaningful association among entity types”  Relationship instance is “an association among entity instances 11

12 Relationship of E-R Model 2  Represented by a diamond in the original Chen notation and by a connecting line  Connectivity label (name) is a verb phrase in sentence-case  Either an active or passive form (e.g., manages or managed by) 12

13 Degree of a Relationship 1  The number of entity types that participate in a relationship.  Unary (recursive) relationship is a relationship between the instances of one entity type  Examples are marriage and supervision in an organization 13

14 Degree of a Relationship 2  Binary relationship is a relationship between instances of two entity types.  Binary relationship is most common  Ternary relationship is a simultaneous relationship among instances of three entity types. 14

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16 Cardinality (Constraint) 1  “ The number of instances of entity B that can (or must) be associated with each instance of entity A ”  Cardinality of a relationship expresses the minimum and maximum number of entity occurrences associated with one occurrence of the related entity. 16

17 Cardinality (Constraint) 2  Minimum cardinality: minimum number of instances of entity B that may be associated with each instance of entity A  Maximum cardinality: maximum number of instances of entity B that may be associated with each instance of entity A  Zero (0) cardinality implies “ optional, ” cardinality one (1) means “ mandatory ” 17

18 Cardinality (Constraint) 3  (0,1) zero minimum or one maximum; optional  (1,1) one and only one; mandatory  (0, N) one or many; optional  (1,N) one or many; mandatory  Symbols are used instead of numbers in ERD 18

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22 Normalization  Normalization simplifies a database to make it compliant with the concept of the normal form.  Eliminate duplicate and/or abnormal records 22

23 CASE Tools  CASE tools are very useful in system design and development stage, facilitating communications among stakeholders.  Professional CASE tools, CaseStudio, Microsoft Visio (Professional Edition)  MySql Workbench  http://dev.mysql.com/downloads/workbenc h/ 23

24 An Example of CASE Tools  CASE Studio II and MySql Workbench  GUI Provides flexible ways to modify.  Define the database structure that matches with the E-R diagram  Generate SQL commands to create corresponding tables based on E-R diagram designed. 24

25 E-R Diagram (CaseStudio 2)

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