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Conceptual Data Modeling Chapter 9. The Entity-Relationship Model/Diagram. Agenda. Conceptual Data Modeling—what and why? Terminology How to Lots of examples. Learning Objectives. After this chapter, you should be able to:

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conceptual data modeling chapter 9

Conceptual Data ModelingChapter 9

The Entity-Relationship Model/Diagram

agenda
Agenda
  • Conceptual Data Modeling—what and why?
  • Terminology
  • How to
  • Lots of examples
learning objectives
Learning Objectives
  • After this chapter, you should be able to:
    • Define key data-modeling terms (entity type, attribute, multivalued attribute, relationship, degree, cardinality, associative entity, etc.)
    • Draw an E-R diagram to represent common scenarios
    • Explain the role of conceptual data modeling in the overall analysis and design of an information system
    • Distinguish between types of relationships (unary, binary, ternary, etc.)
    • Relate data modeling the process and logic modeling as different views of describing an information system
for starters
For Starters:

1. What do we mean by “conceptual data modeling”?

2. Why is it important?

3. How is it different than other “views” of the business system such as process models (DFDs)?

e r model constructs
E-R Model Constructs
  • Entity - person, place, object, event, concept
  • Entity Type versus Entity Instance
  • Entity Type versus System Input, Output, or User
    • Consider the diagram on next page…
    • Treasurer is the person entering data.
    • “Gives-to” and “Summarizes” are business activities, not relationships between entities.
slide8

Example of inappropriate entities

(a) System user (Treasurer) and output (Expense Report) shown as entities

e r model constructs10
E-R Model Constructs
  • Strong versus Weak Entity Type
    • Independent versus dependent entity.
    • Identifying owner.
    • Identifying relationship.
    • Weak entity identifier is its partial identifier combined with that of its owner.
e r model constructs12
E-R Model Constructs
  • Attribute - property or characteristic of an entity type
  • Simple versus Composite Attribute
  • Single-Valued versus Multivalued Attribute
  • Stored versus Derived Attributes
e r model constructs15
E-R Model Constructs
  • Identifier or Key - An attribute (or combination of attributes) that uniquely identifies individual instances of an entity type.
  • Simple Key versus Composite Key
  • Candidate Key
slide16

Simple and composite key attributes:

Here: Simple key attribute

relationships
Relationships
  • Relationship Type versus Instance
  • Degree of a Relationship - number of entity types that participate in it.
    • Unary (or Recursive) Relationship
slide19

Relationship types and instances:

(a) Relationship type (Completes)

relationships21
Relationships
  • Types
    • Unary Relationship (previously mentioned)
    • Binary Relationship
    • Ternary Relationship
  • Attributes of Relationships
    • Many-to-Many
    • Associative Entities (Gerunds)
      • All relationships involved are “many”
      • Result has independent meaning
      • Gerund has one or more non-key attributes
slide25

A relationship with an attribute

…as an associative entity

relationships26
Relationships
  • Cardinality Constraints - the number of instances of one entity that can or must be associated with each instance of another entity
    • Minimum Cardinality
      • If zero, then optional.
    • Maximum Cardinality
    • Mandatory One - when min & max both = 1.
slide29

Examples of cardinality constraints

(a) Mandatory cardinalities

other special case types of relationships
Other “Special Case” Types of Relationships
  • Modeling Time-Dependent Data
    • Time Stamps
  • Multiple Relationship - more than one relationship between the same entity types
supertypes and subtypes
Supertypes and Subtypes
  • Subtype: a subrouping of the entities in an entity type that shares common attributes or relationships distinct from other subtypes
  • Supertype: a generic entity type that has a relationship with one or more subtype
problems exercises
Problems/Exercises
  • P&Es from Chapter 9:
  • 4
  • 5
  • 8
  • 16
p e 4
P&E #4

A software training program is divided into training modules, and each module is described by module name and the approximate practice time. Each module sometimes has prerequisite modules. Model this situation of training program with an E-R diagram.

p e 5
P&E #5

Each semester, each student must be assigned an advisor who counsels students about degree requirements and helps students register for classes. Students must register for classes with the help of an advisor, but if their assigned advisor is not available, they may register with any advisor. We must keep track of students, their assigned advisor, and with whom the student registered for the current term. Represent this situation of students and advisors with an E-R diagram.

What if some students are also advisors? Hint: use supertypes/subtypes.

p e 8
P&E #8
  • How many PROJECTs can an employee work on?
  • What is the degree of the Includes relationship?
  • Are there any associative entities on this diagram?
  • How else could the attribute Skill be modeled?
  • Is it possible to attach any attributes to the Includes relationship?
  • Could TASK be modeled as an associative entity?
figure 9 23
Figure 9-23

[Alternate Representation]