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Data Modeling

Data Modeling. Advanced Concepts. Common Modeling Situations. Unary relationships Binary relationships Ternary relationships Attributive or Weak Entities Associative or Intersection Entities Supertypes and Subtypes. Degree of Relationship. Degree

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Data Modeling

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  1. Data Modeling Advanced Concepts

  2. Common Modeling Situations • Unary relationships • Binary relationships • Ternary relationships • Attributive or Weak Entities • Associative or Intersection Entities • Supertypes and Subtypes

  3. Degree of Relationship • Degree • Number of entity types that participate in a relationship • Three cases • Unary • A relationship between two instances of one entity type • Binary • A relationship between the instances of two entity types • Ternary • A simultaneous relationship among the instances of three entity types • Not the same as three binary relationships

  4. Figure 10-6Example relationships of different degrees

  5. Which type of relationship is this? Customers (Parent) Orders (Child) cust_idcust_name 100 Slick Willy, Inc. 200 George_W, Co. 300 Gore, Ltd. … ord no cust_idord_date 2100 200 13-Sep-2000 2101 100 14-Nov-2000 2102 100 23-Dec-2000 2103 100 24-Dec-2000 … A customer places many orders. An order is placed by only one customer. “An instance of the entity customer is related to one or many instances of orders. An instance of order is related to only one instance of customer.”

  6. Which type of relationship is this? • Are these the same statements? • A CD appears on several orders. • An order may have many CDS on it.

  7. Entity-Relationship (E-R) ModelingKey Terms • Attributive or Weak Entity • An entity than cannot exist without the existence of another entity. • Examples. What would be a weak entity for • A DePaul Course? • An employee? • A product? • Associative entity • An entity type that associates the instances of one or more entity types and contains attributes that are peculiar to the relationship between those entity instances

  8. Multivalued Attributes • How do we model the situation where an entity has an attribute describing it, but • The attribute may take on more than one value for each entity instance • The multivalued attribute can be represented on an E-R Diagram in two ways: • double-lined ellipse • weak entity

  9. Depicting Multivalued Attributes See pages 316-317. Which way is better? What should the identifier of DEPENDENT be?

  10. Depicting Associative Entities See pages 323-324. Which way is better? What should the identifier of CERTIFICATE be?

  11. Depicting M:M relationships • Create an intersection entity (line item). • Move the “M’s” are adjacent to the intersection entity. 3. The “1” side goes on the original entities.

  12. Supertypes and Subtypes • A supertype is a generic entity type that has a relationship with one or more subtypes. • A subtype is a subgrouping of the entities in an entity type that is meaningful to the organization and that shares common attributes or relationships distinct from other subgroupings. • Examples • Customers and Preferred Customers • Students, graduate, PhD, undergraduate, full-time, part-time • Why bother?

  13. Supertype/Subtype RulesSpecialization • Does the instance of the supertype have to be a member of a subtype? • If yes, Total Specialization (double line) • If no, Partial Specialization (single line) • It says supertypes are allowed not to belong to a subtype. • Examples—which rule of specialization applies? • Customers and Preferred Customers • Students, graduate, PhD, undergraduate, full-time, part-time

  14. Supertype/Subtype RulesDisjoint/Overlap • Can an instance of the supertype be a member of more than one subtype? • If yes, Overlap (letter “o”) • If no, Disjoint (letter “d”) • Examples—which rule of specialization applies? • Friends, countrymen, Romans • Students, graduate, PhD, undergraduate, full-time, part-time

  15. Supertype/Subtype Example Page 326. Is this diagram correct? What about the “Is assigned” relationship?

  16. Another example. Page 327. Does the model allow for: Student Employees? Staff members teaching? Simultaneous Grad/undergrad students? A “non-employee/alumnus/student” PERSON?

  17. Business Rules • Entity integrity • Each entity instance has a unique identifier. • The identifier value cannot be empty. • Referential integrity • The value or existence of an attribute in one relation depends on the value or existence of the same attribute occurring in another relation • More on this in IS422 • Domains • Triggering operations

  18. Domains • The set of all data types and ranges of values that an attribute can assume • Several advantages • Verify that the values for an attribute are valid • Ensure that various data manipulation operations are logical • Help conserve effort in describing attribute characteristics

  19. Triggering Operations • An assertion or rule that governs the validity of data manipulation operations such as insert, update and delete • Includes the following components: • User rule • Statement of the business rule to be enforced by the trigger • Event • Data manipulation operation that initiates the operation • Entity Name • Name of entity being accessed or modified • Condition • Condition that causes the operation to be triggered • Action • Action taken when the operation is triggered • Where would you say the responsibility for data integrity lies—in the application programs or the database management system?

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