1. © 2009 Pearson Education, Inc. Publishing as Prentice Hall 1 Modeling Data in the Organization Chapters 3 + 4: Modern Database Management 9 th Edition Jeffrey A. Hoffer, Mary B. Prescott, Heikki Topi UNIT 03:

2. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 2 Objectives Definition of terms Definition of terms Importance of data modeling Importance of data modeling Write good names and definitions for entities, relationships, and attributes Write good names and definitions for entities, relationships, and attributes Distinguish unary, binary, and ternary relationships Distinguish unary, binary, and ternary relationships Model different types of attributes, entities, relationships, and cardinalities Model different types of attributes, entities, relationships, and cardinalities Draw E-R diagrams for common business situations Draw E-R diagrams for common business situations Convert many-to-many relationships to associative entities Convert many-to-many relationships to associative entities Model time-dependent data using time stamps Model time-dependent data using time stamps

3. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 3 Business Rules Statements that define or constrain some aspect of the business Statements that define or constrain some aspect of the business Assert business structure Assert business structure Control/influence business behavior (prevent, cause, or suggest things to happen) Control/influence business behavior (prevent, cause, or suggest things to happen) Expressed in terms familiar to end users Expressed in terms familiar to end users Automated through DBMS software Automated through DBMS software

4. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Examples Every student in the university must have a faculty advisor. Every student in the university must have a faculty advisor. A student is any person who has applied for admission or taken a course or training program. A student is any person who has applied for admission or taken a course or training program. A student may register for a section of a course only if s/he has successfully completed the prerequisite for that course. A student may register for a section of a course only if s/he has successfully completed the prerequisite for that course. A preferred customer qualifies for a 10 percent discount, unless he has an overdue account balance. A preferred customer qualifies for a 10 percent discount, unless he has an overdue account balance. 4

5. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Business Rules Business rules are not universal. Business rules are not universal. The rules and policies of an organization may change over time. The rules and policies of an organization may change over time. Business rules appear in descriptions of business functions, events, policies, units, stakeholders, and other objects. Business rules appear in descriptions of business functions, events, policies, units, stakeholders, and other objects. They can be found in interview notes and group information requirements. They can be found in interview notes and group information requirements. 5

6. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Types of Business Rules Basic business rules are data names and definitions. Basic business rules are data names and definitions. Constraint business rules state constraints on data objects. Constraint business rules state constraints on data objects. Other business rules govern the people, places, events, processes, network, and the objectives of the organization. Other business rules govern the people, places, events, processes, network, and the objectives of the organization. 6

7. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Importance Business Rules are important in database modeling because they govern how data are handled (creating, updating, removing) and stored. Business Rules are important in database modeling because they govern how data are handled (creating, updating, removing) and stored. Thus they must be described along with the data to which they are related. Thus they must be described along with the data to which they are related. 7

8. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Data Modeling Documenting rules and policies of an organization that govern data is exactly what data modeling is all about. Documenting rules and policies of an organization that govern data is exactly what data modeling is all about. Your job as a database analyst is to: Your job as a database analyst is to: Identify and understand business rules that govern data. Identify and understand business rules that govern data. Represent those rules so that they can be unambiguously understood by information systems developers, and Represent those rules so that they can be unambiguously understood by information systems developers, and Implement those rules in database technology. Implement those rules in database technology. 8

9. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 9 A Good Business Rule Is: Declarative–what, not how Declarative–what, not how Precise–clear, agreed-upon meaning Precise–clear, agreed-upon meaning Atomic–one statement Atomic–one statement Consistent–internally and externally Consistent–internally and externally Expressible–structured, natural language Expressible–structured, natural language Distinct–non-redundant Distinct–non-redundant Business-oriented–understood by business people Business-oriented–understood by business people

10. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 10 A Good Data Name Is: Related to business, not technical, characteristics Related to business, not technical, characteristics Meaningful and self-documenting Meaningful and self-documenting Unique Unique Readable Readable Composed of words from an approved list Composed of words from an approved list Repeatable Repeatable Follows standard syntax Follows standard syntax

11. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 11 Data Definitions Explanation of a term or fact Explanation of a term or fact Term–word or phrase with specific meaning Term–word or phrase with specific meaning Fact–association between two or more terms Fact–association between two or more terms Guidelines for good data definition Guidelines for good data definition Gathered in conjunction with systems requirements Gathered in conjunction with systems requirements Accompanied by diagrams Accompanied by diagrams Concise description of essential data meaning Concise description of essential data meaning Achieved by consensus, and iteratively refined Achieved by consensus, and iteratively refined

12. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Examples of Terms and Facts Terms: Terms: Course, section, rental car, flight, reservation, and passenger. Course, section, rental car, flight, reservation, and passenger. Facts: Facts: A course is a module of instruction in a particular subject area. A course is a module of instruction in a particular subject area. A customer may request a model of car from a rental branch on a particular date. A customer may request a model of car from a rental branch on a particular date. 12

13. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 13 E-R Model Constructs Entities: Entities: Entity instance–person, place, object, event, concept (often corresponds to a row in a table) Entity instance–person, place, object, event, concept (often corresponds to a row in a table) Entity Type–collection of entities (often corresponds to a table) Entity Type–collection of entities (often corresponds to a table) Relationships: Relationships: Relationship instance–link between entities (corresponds to primary key-foreign key equivalencies in related tables) Relationship instance–link between entities (corresponds to primary key-foreign key equivalencies in related tables) Relationship type–category of relationship…link between entity types Relationship type–category of relationship…link between entity types Attribute– property or characteristic of an entity or relationship type (often corresponds to a field in a table) Attribute– property or characteristic of an entity or relationship type (often corresponds to a field in a table)

14. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 14 Sample E-R Diagram (Figure 3-1)

15. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 15 Relationship degrees specify number of entity types involved Entity symbols A special entity that is also a relationship Relationship symbols Relationship cardinalities specify how many of each entity type is allowed Attribute symbols Basic E-R notation (Figure 3-2)

16. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 16 Types of Entities A strong entity type is one that exists independently of other entity types. A strong entity type is one that exists independently of other entity types. Examples: Employee, student, course, automobile. Examples: Employee, student, course, automobile. Instances always have a unique characteristic distinguish each occurrence of that entity. Instances always have a unique characteristic distinguish each occurrence of that entity. Identifier underlined with single line Identifier underlined with single line A weak entity type is one whose existence depends on other entity type. A weak entity type is one whose existence depends on other entity type. Example: Dependent Example: Dependent does not have a unique identifier (only a partial identifier, a characteristic that serves as a partial identifier). does not have a unique identifier (only a partial identifier, a characteristic that serves as a partial identifier).

17. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 17 Strong entity Weak entity Identifying relationship (Figure 3-5)

18. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Types of Entities An associative entity is an entity type that associate the instances of one or more entity types and contain attributes that are particular to the relationship between those entity instances. An associative entity is an entity type that associate the instances of one or more entity types and contain attributes that are particular to the relationship between those entity instances. Example: certificate offered to an employee after completing a course of study. Example: certificate offered to an employee after completing a course of study. 18

19. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 19 What Should an Entity Be? SHOULD BE: SHOULD BE: An object that will have many instances in the database An object that will have many instances in the database An object that will be composed of multiple attributes An object that will be composed of multiple attributes An object that we are trying to model An object that we are trying to model SHOULD NOT BE: SHOULD NOT BE: A user of the database system A user of the database system An output of the database system (e.g., a report) An output of the database system (e.g., a report)

20. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 20 Inappropriate entities Systemuser System output Figure 3-4 Example of inappropriate entities Appropriate entities

21. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 21 Attributes Attribute–property or characteristic of an entity or relationship type Attribute–property or characteristic of an entity or relationship type Classifications of attributes: Classifications of attributes: Required versus Optional Attributes Required versus Optional Attributes Simple versus Composite Attribute Simple versus Composite Attribute Single-Valued versus Multivalued Attribute Single-Valued versus Multivalued Attribute Stored versus Derived Attributes Stored versus Derived Attributes Identifier Attributes Identifier Attributes

22. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 22 Identifiers (Keys) Identifier (Key)–an attribute (or combination of attributes) that uniquely identifies individual instances of an entity type Identifier (Key)–an attribute (or combination of attributes) that uniquely identifies individual instances of an entity type Simple versus Composite Identifier Simple versus Composite Identifier Candidate Identifier–an attribute that could be a key…satisfies the requirements for being an identifier Candidate Identifier–an attribute that could be a key…satisfies the requirements for being an identifier

23. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 23 Characteristics of Identifiers Will not change in value Will not change in value Will not be null Will not be null No intelligent identifiers (e.g., containing locations or people that might change) No intelligent identifiers (e.g., containing locations or people that might change) Substitute new, simple keys for long, composite keys Substitute new, simple keys for long, composite keys

24. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 24 Figure 3-7 A composite attribute An attribute broken into component parts Figure 3-8 Entity with multivalued attribute (Skill) and derived attribute (Years_Employed) Multivalued an employee can have more than one skill Derived from date employed and current date

25. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 25 Figure 3-9 Simple and composite identifier attributes The identifier is boldfaced and underlined

26. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 26 Figure 3-19 Simple example of time-stamping This attribute is both multivalued and composite

27. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 27 More on Relationships Relationship Types vs. Relationship Instances Relationship Types vs. Relationship Instances The relationship type is modeled as lines between entity types…the instance is between specific entity instances The relationship type is modeled as lines between entity types…the instance is between specific entity instances Relationships can have attributes Relationships can have attributes These describe features pertaining to the association between the entities in the relationship These describe features pertaining to the association between the entities in the relationship Two entities can have more than one type of relationship between them (multiple relationships) Two entities can have more than one type of relationship between them (multiple relationships) Associative Entity–combination of relationship and entity Associative Entity–combination of relationship and entity

28. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 28 Figure 3-10 Relationship types and instances a) Relationship type b) Relationship instances

29. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 29 Degree of Relationships Degree of a relationship is the number of entity types that participate in it Degree of a relationship is the number of entity types that participate in it Unary Relationship Unary Relationship Binary Relationship Binary Relationship Ternary Relationship Ternary Relationship

30. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 30 Degree of relationships – from Figure 3-2 Entities of two different types related to each other Entities of three different types related to each other One entity related to another of the same entity type

31. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 31 Cardinality of Relationships One-to-One One-to-One Each entity in the relationship will have exactly one related entity Each entity in the relationship will have exactly one related entity One-to-Many One-to-Many An entity on one side of the relationship can have many related entities, but an entity on the other side will have a maximum of one related entity An entity on one side of the relationship can have many related entities, but an entity on the other side will have a maximum of one related entity Many-to-Many Many-to-Many Entities on both sides of the relationship can have many related entities on the other side Entities on both sides of the relationship can have many related entities on the other side

32. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 32 Cardinality Constraints Cardinality Constraints—the number of instances of one entity that can or must be associated with each instance of another entity Cardinality Constraints—the number of instances of one entity that can or must be associated with each instance of another entity Minimum Cardinality Minimum Cardinality If zero, then optional If zero, then optional If one or more, then mandatory If one or more, then mandatory Maximum Cardinality Maximum Cardinality The maximum number The maximum number

33. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 33 Figure 3-12 Examples of relationships of different degrees a) Unary relationships

34. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 34 Figure 3-12 Examples of relationships of different degrees (cont.) b) Binary relationships

35. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 35 Figure 3-12 Examples of relationships of different degrees (cont.) c) Ternary relationship Note: a relationship can have attributes of its own

36. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 36 Figure 3-17 Examples of cardinality constraints a) Mandatory cardinalities A patient must have recorded at least one history, and can have many A patient history is recorded for one and only one patient

37. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 37 Figure 3-17 Examples of cardinality constraints (cont.) b) One optional, one mandatory An employee can be assigned to any number of projects, or may not be assigned to any at all A project must be assigned to at least one employee, and may be assigned to many

38. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 38 Figure 3-17 Examples of cardinality constraints (cont.) c) Optional cardinalities A person is married to at most one other person, or may not be married at all

39. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 39 Entities can be related to one another in more than one way Figure 3-21 Examples of multiple relationships a) Employees and departments

40. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 40 Figure 3-21 Examples of multiple relationships (cont.) b) Professors and courses (fixed lower limit constraint) Here, min cardinality constraint is 2

41. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 41 Figure 3-15a and 3-15b Multivalued attributes can be represented as relationships simple composite

42. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 42 Associative Entities An entity –has attributes An entity –has attributes A relationship –links entities together A relationship –links entities together When should a relationship with attributes instead be an associative entity ? When should a relationship with attributes instead be an associative entity ? All relationships for the associative entity should be many All relationships for the associative entity should be many The associative entity could have meaning independent of the other entities The associative entity could have meaning independent of the other entities The associative entity preferably has a unique identifier, and should also have other attributes The associative entity preferably has a unique identifier, and should also have other attributes The associative entity may participate in other relationships other than the entities of the associated relationship The associative entity may participate in other relationships other than the entities of the associated relationship Ternary relationships should be converted to associative entities Ternary relationships should be converted to associative entities

43. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 43 Figure 3-11a A binary relationship with an attribute Here, the date completed attribute pertains specifically to the employee’s completion of a course…it is an attribute of the relationship

44. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 44 Figure 3-11b An associative entity (CERTIFICATE) Associative entity is like a relationship with an attribute, but it is also considered to be an entity in its own right Note that the many-to-many cardinality between entities in Figure 3-11a has been replaced by two one-to-many relationships with the associative entity

45. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 45 Figure 3-13c An associative entity – bill of materials structure This could just be a relationship with attributes…it’s a judgment call

46. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 46 Figure 3-18 Ternary relationship as an associative entity

47. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 47 Microsoft Visio Notation for Pine Valley Furniture E-R diagram (Figure 3-22) Different modeling software tools may have different notation for the same constructs

48. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 48 Supertypes and Subtypes Subtype: A subgrouping of the entities in an entity type that has attributes distinct from those in other subgroupings Subtype: A subgrouping of the entities in an entity type that has attributes distinct from those in other subgroupings Supertype: A generic entity type that has a relationship with one or more subtypes Supertype: A generic entity type that has a relationship with one or more subtypes Attribute Inheritance: Attribute Inheritance: Subtype entities inherit values of all attributes of the supertype Subtype entities inherit values of all attributes of the supertype An instance of a subtype is also an instance of the supertype An instance of a subtype is also an instance of the supertype

49. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 49 Figure 4-1 Basic notation for supertype/subtype notation a) EER notation

50. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 50 Different modeling tools may have different notation for the same modeling constructs b) Microsoft Visio Notation Figure 4-1 Basic notation for supertype/subtype notation (cont.)

51. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 51 Figure 4-2 Employee supertype with three subtypes All employee subtypes will have emp nbr, name, address, and date hired Each employee subtype will also have its own attributes

52. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 52 Relationships and Subtypes Relationships at the supertype level indicate that all subtypes will participate in the relationship Relationships at the supertype level indicate that all subtypes will participate in the relationship The instances of a subtype may participate in a relationship unique to that subtype. In this situation, the relationship is shown at the subtype level The instances of a subtype may participate in a relationship unique to that subtype. In this situation, the relationship is shown at the subtype level

53. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 53 Figure 4-3 Supertype/subtype relationships in a hospital Both outpatients and resident patients are cared for by a responsible physician Only resident patients are assigned to a bed

54. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 54 Generalization and Specialization Generalization: The process of defining a more general entity type from a set of more specialized entity types. BOTTOM-UP Generalization: The process of defining a more general entity type from a set of more specialized entity types. BOTTOM-UP Specialization: The process of defining one or more subtypes of the supertype and forming supertype/subtype relationships. TOP-DOWN Specialization: The process of defining one or more subtypes of the supertype and forming supertype/subtype relationships. TOP-DOWN

55. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 55 Figure 4-4 Example of generalization a) Three entity types: CAR, TRUCK, and MOTORCYCLE All these types of vehicles have common attributes

56. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 56 Figure 4-4 Example of generalization (cont.) So we put the shared attributes in a supertype Note: no subtype for motorcycle, since it has no unique attributes b) Generalization to VEHICLE supertype

57. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 57 Figure 4-5 Example of specialization a) Entity type PART Only applies to manufactured parts Applies only to purchased parts

58. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 58 b) Specialization to MANUFACTURED PART and PURCHASED PART Note: multivalued attribute was replaced by an associative entity relationship to another entity Created 2 subtypes Figure 4-5 Example of specialization (cont.)

59. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 59 Constraints in Supertype/ Completeness Constraint Completeness Constraints : Whether an instance of a supertype must also be a member of at least one subtype Completeness Constraints : Whether an instance of a supertype must also be a member of at least one subtype Total Specialization Rule: Yes (double line) Total Specialization Rule: Yes (double line) Partial Specialization Rule: No (single line) Partial Specialization Rule: No (single line)

60. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 60 Figure 4-6 Examples of completeness constraints a) Total specialization rule A patient must be either an outpatient or a resident patient

61. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 61 b) Partial specialization rule A vehicle could be a car, a truck, or neither Figure 4-6 Examples of completeness constraints (cont.)

62. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 62 Constraints in Supertype/ Disjointness constraint Disjointness Constraints : Whether an instance of a supertype may simultaneously be a member of two (or more) subtypes Disjointness Constraints : Whether an instance of a supertype may simultaneously be a member of two (or more) subtypes Disjoint Rule: An instance of the supertype can be only ONE of the subtypes Disjoint Rule: An instance of the supertype can be only ONE of the subtypes Overlap Rule: An instance of the supertype could be more than one of the subtypes Overlap Rule: An instance of the supertype could be more than one of the subtypes

63. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 63 a) Disjoint rule Figure 4-7 Examples of disjointness constraints A patient can either be outpatient or resident, but not both

64. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 64 b) Overlap rule A part may be both purchased and manufactured Figure 4-7 Examples of disjointness constraints (cont.)

65. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 65 Constraints in Supertype/ Subtype Discriminators Subtype Discriminator : An attribute of the supertype whose values determine the target subtype(s) Subtype Discriminator : An attribute of the supertype whose values determine the target subtype(s) Disjoint – a simple attribute with alternative values to indicate the possible subtypes Disjoint – a simple attribute with alternative values to indicate the possible subtypes Overlapping – a composite attribute whose subparts pertain to different subtypes. Each subpart contains a boolean value to indicate whether or not the instance belongs to the associated subtype Overlapping – a composite attribute whose subparts pertain to different subtypes. Each subpart contains a boolean value to indicate whether or not the instance belongs to the associated subtype

66. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 66 Figure 4-8 Introducing a subtype discriminator ( disjoint rule) A simple attribute with different possible values indicating the subtype

67. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 67 Figure 4-9 Subtype discriminator ( overlap rule) A composite attribute with sub-attributes indicating “yes” or “no” to determine whether it is of each subtype

68. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 68 Figure 4-10 Example of supertype/subtype hierarchy

69. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 69 Entity Clusters EER diagrams are difficult to read when there are too many entities and relationships EER diagrams are difficult to read when there are too many entities and relationships Solution: Group entities and relationships into entity clusters Solution: Group entities and relationships into entity clusters Entity cluster: Set of one or more entity types and associated relationships grouped into a single abstract entity type Entity cluster: Set of one or more entity types and associated relationships grouped into a single abstract entity type

70. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 70 Figure 4-13a Possible entity clusters for Pine Valley Furniture in Microsoft Visio Related groups of entities could become clusters

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72. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 72

73. Chapter 3 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 73 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall