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Conceptual Data Modeling Chapter 9

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  1. Conceptual Data ModelingChapter 9 The Entity-Relationship Model/Diagram

  2. Agenda • Conceptual Data Modeling—what and why? • Terminology • How to • Lots of examples

  3. 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

  4. 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)?

  5. Basic E-R Notation

  6. Figure 9-3: Sample Conceptual Data Model

  7. 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.

  8. Example of inappropriate entities (a) System user (Treasurer) and output (Expense Report) shown as entities

  9. Corrected E-R model with only the necessary entities

  10. 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.

  11. Example of a weak entity

  12. 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

  13. A composite attribute

  14. Entity with a multivalued attribute (Skill) and derived attribute (Years_Employed)

  15. 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

  16. Simple and composite key attributes: Here: Simple key attribute

  17. And now: Composite key attribute

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

  19. Relationship types and instances: (a) Relationship type (Completes)

  20. …as opposed to relationship instances (here)

  21. 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

  22. Unary Relationship Example

  23. Binary Relationship Examples

  24. (c ) Ternary relationships

  25. A relationship with an attribute …as an associative entity

  26. 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.

  27. Introducing cardinality constraints: (a) Basic relationship

  28. (b) Relationship with cardinality constraints:

  29. Examples of cardinality constraints (a) Mandatory cardinalities

  30. (b) One optional, one mandatory cardinality

  31. Cardinality constraints in a ternary relationship

  32. Other “Special Case” Types of Relationships • Modeling Time-Dependent Data • Time Stamps • Multiple Relationship - more than one relationship between the same entity types

  33. Simple example of time stamping

  34. (b) Why two separate relationships here?

  35. 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

  36. Figure 9-19: Example of supertypes/subtypes

  37. Problems/Exercises • P&Es from Chapter 9: • 4 • 5 • 8 • 16

  38. 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.

  39. 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.

  40. 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?

  41. Figure 9-23 [Alternate Representation]

  42. P&E #16 – Draw ERD