1. Chapter 2
Data Model
Database Systems: Design, Implementation, and Management, Sixth Edition, Rob and Coronel

2. In this chapter, you will learn:
Why data models are important
About the basic data-modeling building blocks
What business rules are and how they affect database design
How the major data models evolved, and their advantages and disadvantages
How data models can be classified by level of abstraction

3. The Importance of Data Models
Relatively simple representation, usually graphical, of complex real-world data structures
Communications tool to facilitate interaction among the designer, the applications programmer, and the end user
Good database design uses an appropriate data model as its foundation
End-users have different views and needs for data
Data model organizes data for various users

4. Data Model Basic Building Blocks
Entity – is anything about which data are to be collected and stored
Attribute – is a characteristic of an entity
Relationship – describes an association among (two or more) entities
One-to-many (1:M) relationship
Many-to-many (M:N or M:M) relationship
One-to-one (1:1) relationship
Constraint - a restriction placed on the data

5. Business Rules
How do database designers go about determining the entities, attributes, and relationships that will build a data model?
Business Rules – Brief, precise, and unambiguous description of a policy, procedure, or principle within a specific organization’s environment

6. Business Rules (continued)
Must be rendered in writing
Must be kept up to date
Sometimes are external to the organization
Must be easy to understand and widely disseminated
Describe characteristics of the data as viewed by the company

7. Examples of Business Rules
A customer may generate many invoices.
Each invoice is generated by only one customer.

8. Sources of Business Rules
Company managers
Policy makers
Department managers
Written documentation
Procedures
Standards
Operations manuals
Direct interviews with end users

9. Importance of Business Rules
Standardize company’s view of data
Constitute a communications tool between users and designers
Allow designer to understand the nature, role, and scope of data
Allow designer to understand business processes
Allow designer to develop appropriate relationship participation rules and constraints

10. Translating Business Rules into Data Model Components
Generally, nouns translate into entities
Verbs translate into relationships among entities
Relationships are bi-directional
A customer may generate many invoices.
Each invoice is generated by only one customer.

11. The Evolution of Data Models

12. The Evolution of Data Models
Hierarchical
Network
Relational
Entity relationship
Object oriented

13. The Hierarchical Model
Developed in the 1960s to manage large amounts of data for complex manufacturing projects
Basic logical structure is represented by an upside-down “tree”

14. Hierarchical Database Model
Logically represented by an upside down tree
Each parent can have many children
Each child has only one parent

15. Hierarchical Database Model
Advantages
Conceptual simplicity (The relationship between the various layers of the model is logically simple)
Database security and integrity
Data independence
Efficiency
Disadvantages
Complex implementation
Difficult to manage and lack of standards
Lacks structural independence
Applications programming and use complexity
Implementation limitations

16. The Network Model Created to
Represent complex data relationships more effectively
Improve database performance
Impose a database standard

17. The Network Model (continued)
Schema
Conceptual organization of entire database as viewed by the database administrator
Subschema
Defines database portion “seen” by the application programs that actually produce the desired information from data contained within the database

18. The Network Model (continued)
Schema Data Definition Language (DDL)
Enables database administrator to define schema components
Subschema DDL
Allows application programs to define database components that will be used
Data Management Language (DML)
Defines the environment in which data can be managed
Works with the data in the database

19. The Network Model (continued)
Resembles hierarchical model
Collection of records in 1:M relationships
Set
Relationship
Composed of at least two record types
Owner
Equivalent to the hierarchical model’s parent
Member
Equivalent to the hierarchical model’s child

20. Network Database Model
Each record can have multiple parents
Composed of sets
Each set has owner record and member record
Member may have several owners
Collection of records in 1:M relationships

21. Network Database Model
Advantages
Conceptual simplicity
Handles more relationship types
Data access flexibility
Promotes database integrity
Data independence
Conformance to standards
Disadvantages
System complexity
Lack of structural independence

22. Relational Database Model
Developed by Codd (IBM) in 1970
Perceived by user as a collection of tables for data storage
Tables are a series of row/column intersections
Tables related by sharing common entity characteristic(s) (Figure 2.4)
Relational table is purely logical structure
How data are physically stored in the database is of no concern to the user or the designer

23. Linking Relational Tables
AGENT_CODE

24. The Relational Model (continued)
Relational diagram Representation of relational database’s entities, attributes within those entities, and relationships between those entities
AGENT_CODE

25. The Relational Model (continued)
Rise to dominance due in part to its powerful and flexible query language
Structured Query Language (SQL) allows the user to specify what must be done without specifying how it must be done
SQL-based relational database application involves:
User interface
A set of tables stored in the database
SQL engine

26. Relational Database Model
Advantages
Structural independence
Improved conceptual simplicity
Easier database design, implementation, management, and use
Ad hoc query capability with SQL
Powerful database management system

27. Relational Database Model
Disadvantages
Substantial hardware and system software overhead
Poor design and implementation is made easy

28. Entity Relationship Model
Widely accepted and adapted graphical tool for data modeling
Introduced by Chen in 1976
Graphical representation of entities and their relationships in a database structure

29. The ER Model — Basic Structure
Entity relationship diagram (ERD)
Uses graphic representations to model database components
Entity is mapped to a relational table
Entity instance (or occurrence) is row in the relational table
Connectivity labels types of relationships
Diamond connected to related entities through a relationship line
Entity set is collection of like entities
Unfortunately, ERD designers use “entity” as a substitute for “entity set” and we ‘ll conform to that established practice.

30. Relationships: The Basic Chen ERD

31. The Entity Relationship Model
Relationships: The Basic Crow’s Foot ERD

32. Relationships: The Basic Chen ERD

33. Relationships: The Basic Crow’s Foot ERD

34. Entity Relationship Database Model
Complements the relational data model concepts
Represented in an entity relationship diagram (ERD)
Based on entities, attributes, and relationships

35. The Object Oriented Model
Semantic data model (SDM) developed by Hammer and McLeod in 1981
Modeled both data and their relationships in a single structure known as an object
Object-oriented data model OODM is the basis for the object oriented database management system (OODBMS)
OODM is said to be a semantic data model

36. Object-Oriented Database Model
An object is an abstraction of a real-world entity
Attributes describe properties of an object
Objects that share similar characteristics are grouped in class
Classes are organized in a class hierarchy
Inheritance is ability of object to inherit attributes and methods of classes above it

37. The Object Oriented Model (continued)

38. Other Models Extended Relational Data Model (ERDM)
Semantic data model developed in response to increasing complexity of applications
DBMS based on the ERDM often described as an object/relational database management system (O/RDBMS)
Primarily geared to business applications

39. Database Models and the Internet
Internet drastically changed role and scope of database market
OODM and ERDM-O/RDM have taken a backseat to development of databases that interface with Internet
Dominance of Web has resulted in growing need to manage unstructured information

40. Data Models: A Summary
Each new data model capitalized on the shortcomings of previous models
Common characteristics:
Conceptual simplicity without compromising the semantic completeness of the database
Represent the real world as closely as possible

41. Data Models: A Summary

42. Degrees of Data Abstraction
Way of classifying data models
American National Standards Institute/Standards Planning and Requirements Committee (ANSI/SPARC)
Classified data models according to their degree of abstraction (1970s):
Conceptual
External
Internal

43. Degrees of Data Abstraction

44. The External Model End users’ view of the data environment
Requires that the modeler subdivide set of requirements and constraints into functional modules that can be examined within the framework of their external models

45. The External Model (continued)

46. The Conceptual Model Represents global view of the entire database
Representation of data as viewed by the entire organization
Basis for identification and high-level description of main data objects, avoiding details
Most widely used conceptual model is the entity relationship (ER) model

47. The Conceptual Model

48. The Conceptual Model (continued)
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 either hardware or DBMS software have no effect on the database design at the conceptual level

49. 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
Hardware Independent
Software Dependent (DBMS Dependent)

50. The Internal Model

51. The Physical Model
Operates at lowest level of abstraction, describing the way data are saved on storage media such as disks or tapes
Software and hardware dependent
Requires that database designers have a detailed knowledge of the hardware and software used to implement database design

52. Levels of Data Abstraction

53. Summary
A good DBMS will perform poorly with a poorly designed database
A data model is a (relatively) simple abstraction of a complex real-world data-gathering environment
Basic data modeling components are:
Entities
Attributes
Relationships

54. Summary (continued) Hierarchical model
Based on a tree structure composed of a root segment, parent segments, and child segments
Depicts a set of one-to-many (l:M) relationships between a parent and its children
Does not include ad hoc querying capability

55. Summary (continued)
Network model attempts to deal with many of the hierarchical model’s limitations
Relational model:
Current database implementation standard
Much simpler than hierarchical or network design
Object is basic modeling structure of object oriented model
Data modeling requirements are a function of different data views (global vs. local) and level of data abstraction

56. Entity Relationship Database Model
Complements the relational data model concepts
Represented in an entity relationship diagram (ERD)
Based on entities, attributes, and relationships

57. Entity Relationship Database Model
Advantages
Exceptional conceptual simplicity
Visual representation
Effective communication tool
Integrated with the relational database model
Disadvantages
Limited constraint representation
Limited relationship representation (relationships between attributes within entities cannot be represented)
No data manipulation language (DML)
Loss of information content
Relationships between attributes within entities cannot be represented.

58. OO Data Model Advantages Disadvantages Adds semantic content
Visual presentation includes semantic content
Database integrity
Both structural and data independence
Disadvantages
Lack of OODM standards
Complex navigational data access
Steep learning curve
High system overhead slows transactions

59. Database Models and the Internet
Characteristics of “Internet age” databases
Flexible, efficient, and secure Internet access
Easily used, developed, and supported
Supports complex data types and relationships
Seamless interfaces with multiple data sources and structures
Relative conceptual simplicity to make database design and implementation less cumbersome
Many database design, implementation, and application development tools
Powerful DBMS GUI make DBA job easier

60. The Conceptual Model
The conceptual model represents a global view of the data.
It is an enterprise-wide representation of data as viewed by high-level managers.
Entity-Relationship (E-R) model is the most widely used conceptual model.
The conceptual model is_ software independence hardware independence

61. A Conceptual Model for Tiny College

62. Advantages of Conceptual Model
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 either the hardware or the DBMS software have no effect on the database design at the conceptual level

63. The Internal Model
Representation of the database as “seen” by the DBMS
Once a specific DBMS has been selected, the internal model adapts the conceptual model to the DBMS.
The internal model is software-dependent hardware-independence.

64. The External Model
End users’ views of data environment
Each external model is then represented by its own external schema.
Provides subsets of internal view
Makes application program development easier
The external model is DBMS-dependent hardware-independence.
CREATE VIEW CLASS_VIEW AS SELECT (CLASS_ID, CLASS_NAME, PROF_NAME, CLASS_TIME, ROOM_ID) FROM CLASS, PROFESSOR, ROOM WHERE CLASS.PROF_ID = PROFESSOR.PROF_ID AND CLASS.ROOM_ID = ROOM.ROOM_ID;

65. A Division of an Internal Model into External Models

66. The External Models for Tiny College

67. The Physical Model
The physical model operates at the lowest level of abstraction, describing the way data is saved on storage media such as disks or tapes.
Requires that database designers have a detailed knowledge of the hardware and software used to implement database design
The physical model is_ software-dependent hardware-dependent.

68. Database Models
Collection of logical constructs used to represent data structure and data relationships within the database
Conceptual models: logical nature of data representation
focus on the logical nature of the data representation. They are concerned with what is represented rather than how it is represented.
E.g. E-R model
Implementation models: emphasis on how the data are represented in the database
place the emphasis on how the data are represented in the database or on how the data structures are implemented.
E.g. relational database model