1. Department of Mathematics Computer and Information Science1 CS 351: Database Management Systems Christopher I. G. Lanclos Chapter 4

2. Department of Mathematics Computer and Information Science2 Quiz Name Five Relational Set Operators and describe what they do:

3. Department of Mathematics Computer and Information Science3 Answer Name Five Relational Set Operators and describe what they do: – SELECT – UNION – PROJECT – DIFFERENCE – JOIN – PRODUCT – INTERSECT – DIVIDE

4. Department of Mathematics Computer and Information Science4 Chapter 2 Concept Degrees of Data Abstraction – The External Model – The Conceptual Model – The Internal Model – Physical Model

5. Department of Mathematics Computer and Information Science5 Degrees of Data Abstraction Database designer starts with abstracted view, then adds details ANSI Standards Planning and Requirements Committee (SPARC) – Defined a framework for data modeling based on degrees of data abstraction (1970s): External Conceptual Internal

6. Department of Mathematics Computer and Information Science6 The External Model End users’ view of the data environment ER diagrams represent external views External schema: specific representation of an external view – Entities – Relationships – Processes – Constraints

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8. 8 The External Model (cont’d.) Easy to identify specific data required to support each business unit’s operations Facilitates designer’s job by providing feedback about the model’s adequacy Ensures security constraints in database design Simplifies application program development

9. Department of Mathematics Computer and Information Science9 The Conceptual Model Represents global view of the entire database All external views integrated into single global view: conceptual schema ER model most widely used ERD graphically represents the conceptual schema

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11. Department of Mathematics Computer and Information Science11 The Conceptual Model (cont’d.) Provides a relatively easily understood macro level view of data environment Independent of both software and hardware – Does not depend on the DBMS software used to implement the model – Does not depend on the hardware used in the implementation of the model – Changes in hardware or software do not affect database design at the conceptual level

12. Department of Mathematics Computer and Information Science12 The Internal Model Representation of the database as “seen” by the DBMS – Maps the conceptual model to the DBMS Internal schema depicts a specific representation of an internal model Depends on specific database software – Change in DBMS software requires internal model be changed Logical independence: change internal model without affecting conceptual model

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14. Department of Mathematics Computer and Information Science14 The Physical Model Operates at lowest level of abstraction – Describes the way data are saved on storage media such as disks or tapes Requires the definition of physical storage and data access methods Relational model aimed at logical level – Does not require physical-level details Physical independence: changes in physical model do not affect internal model

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16. Department of Mathematics Computer and Information Science16 Objectives In this chapter, students will learn: – The main characteristics of entity relationship components – How relationships between entities are defined, refined, and incorporated into the database design process – How ERD components affect database design and implementation – That real-world database design often requires the reconciliation of conflicting goals

17. Department of Mathematics Computer and Information Science17 The Entity Relationship Model (ERM) ER model forms the basis of an ER diagram ERD represents conceptual database as viewed by end user ERDs depict database’s main components: – Entities – Attributes – Relationships 17

18. Department of Mathematics Computer and Information Science18 Entities Refers to entity set and not to single entity occurrence Corresponds to table and not to row in relational environment In Chen and Crow’s Foot models, entity is represented by rectangle with entity’s name The entity name, a noun, is written in capital letters

19. Department of Mathematics Computer and Information Science19 Attributes Characteristics of entities Chen notation: attributes represented by ovals connected to entity rectangle with a line – Each oval contains the name of attribute it represents Crow’s Foot notation: attributes written in attribute box below entity rectangle

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21. Department of Mathematics Computer and Information Science21 Attributes (cont’d.) Required attribute: must have a value Optional attribute: may be left empty Domain: set of possible values for an attribute – Attributes may share a domain Identifiers: one or more attributes that uniquely identify each entity instance Composite identifier: primary key composed of more than one attribute

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23. Department of Mathematics Computer and Information Science23 Attributes (cont’d.) Composite attribute can be subdivided Simple attribute cannot be subdivided Single-value attribute can have only a single value Multivalued attributes can have many values

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25. Department of Mathematics Computer and Information Science25 Attributes (cont’d.) M:N relationships and multivalued attributes should not be implemented – Create several new attributes for each of the original multivalued attributes’ components – Create new entity composed of original multivalued attributes’ components Derived attribute: value may be calculated from other attributes – Need not be physically stored within database

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27. Department of Mathematics Computer and Information Science27 Relationships Association between entities Participants are entities that participate in a relationship Relationships between entities always operate in both directions Relationship can be classified as 1:M Relationship classification is difficult to establish if only one side of the relationship is known

28. Department of Mathematics Computer and Information Science28 Connectivity and Cardinality Connectivity – Describes the relationship classification Cardinality – Expresses minimum and maximum number of entity occurrences associated with one occurrence of related entity Established by very concise statements known as business rules

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30. Department of Mathematics Computer and Information Science30 Existence Dependence Existence dependence – Entity exists in database only when it is associated with another related entity occurrence Existence independence – Entity can exist apart from one or more related entities – Sometimes such an entity is referred to as a strong or regular entity

31. Department of Mathematics Computer and Information Science31 Relationship Strength Weak (non-identifying) relationships – Exists if PK of related entity does not contain PK component of parent entity Strong (identifying) relationships – Exists when PK of related entity contains PK component of parent entity

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34. Department of Mathematics Computer and Information Science34 Weak Entities Weak entity meets two conditions – Existence-dependent – Primary key partially or totally derived from parent entity in relationship Database designer determines whether an entity is weak based on business rules

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37. Department of Mathematics Computer and Information Science37 Relationship Participation Optional participation – One entity occurrence does not require corresponding entity occurrence in particular relationship Mandatory participation – One entity occurrence requires corresponding entity occurrence in particular relationship

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40. Department of Mathematics Computer and Information Science40 Relationship Degree Indicates number of entities or participants associated with a relationship Unary relationship – Association is maintained within single entity Binary relationship – Two entities are associated Ternary relationship – Three entities are associated

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43. Department of Mathematics Computer and Information Science43 Recursive Relationships Relationship can exist between occurrences of the same entity set – Naturally found within unary relationship

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46. Department of Mathematics Computer and Information Science46 Associative (Composite) Entities Also known as bridge entities Used to implement M:N relationships Composed of primary keys of each of the entities to be connected May also contain additional attributes that play no role in connective process

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49. Department of Mathematics Computer and Information Science49 Developing an ER Diagram Database design is an iterative process – Create detailed narrative of organization’s description of operations – Identify business rules based on description of operations – Identify main entities and relationships from business rules – Develop initial ERD – Identify attributes and primary keys that adequately describe entities – Revise and review ERD

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53. Department of Mathematics Computer and Information Science53 Database Design Challenges: Conflicting Goals Database designers must make design compromises – Conflicting goals: design standards, processing speed, information requirements Important to meet logical requirements and design conventions Design is of little value unless it delivers all specified query and reporting requirements Some design and implementation problems do not yield “clean” solutions

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55. Department of Mathematics Computer and Information Science55 Summary Entity relationship (ER) model – Uses ERD to represent conceptual database as viewed by end user – ERM’s main components: Entities Relationships Attributes – Includes connectivity and cardinality notations 55

56. Department of Mathematics Computer and Information Science56 Summary (cont’d.) Connectivities and cardinalities are based on business rules M:N relationship is valid at conceptual level – Must be mapped to a set of 1:M relationships ERDs may be based on many different ERMs UML class diagrams are used to represent the static data structures in a data model Database designers are often forced to make design compromises