file systems & database 1.5: data models

Chapter 1

FILE SYSTEMS & DATABASE

1.5: Data Models

Oracle

DB2

MS Access

MySQL ITS232Introduction To

Database

Data ModelsThe Importance of Data Models

2

Data models Relatively simple representations, usually

graphical, of complex real-world data structures Facilitate interaction among the designer, the

applications programmer, and the end user End-users have different views and needs for

data Data model organizes data for various users

Data Models Data Model Basic Building Blocks

3

Entity• anything about which data are to be collected

and stored

Attribute• a characteristic of an entity

Relationship• describes an association among entities

Constraint• a restriction placed on the data/user-defined

structures that let you restrict the behaviors of columns/attributes

Data Models Data Model Basic Building Blocks

4

Based on previous IBM DB2 lab, determine:Entity• PERSON, VEHICLE, BUILDING, PLANT, ANIMAL,

etcAttribute• person_name, animal_family, scientific_name,

etcRelationship• 1:1, 1:M, M:N

Constraint• NOT NULL, CHECK, PRIMARY KEY, FOREIGN

KEY, TRIGGER

Data Models Business Rules

5

Brief, precise, and unambiguous descriptions of policies, procedures, or principles within a specific organization

Apply to any organization that stores and uses data to generate information

Description of operations that help to create and enforce actions within that organization’s environment

Data Models Business Rules

6

Must be rendered in writing/available in written form Must be kept up to date Sometimes are external to the organization Must be easy to understand and widely distributed Describe characteristics of the data as viewed by the

company:• corresponds to a table (ERD)Entities

• associations between entitiesRelationships

• characteristics of entitiesAttributes• describe the relationship classification

(min & max)Connectivity

• limitations on the type of data acceptedConstraints

Data Models Discovering Business Rules

7

Sources of Business Rules: Company managers Policy makers Department managers Written documentation

Procedures Standards Operations manuals

Direct interviews with end users


8

Business rules example:

Data Models Translating Business Rules into Data Model Components

9

Standardize company’s view of data Act as a communications tool between users

and designers Allow designer:

to understand the nature, role, and scope of data to understand business processes to develop appropriate relationship participation rules

and constraints Promote creation of an accurate data model


10

Generally Nouns translate into entities Verbs translate into relationships among entities Relationships are bi-directional

Fact finding techniques: The formal process of using techniques such as

interview and questionnaire to collect facts about system, requirements and preferences.

To captures the essential facts necessary to build the required database

What facts are collected? Captured facts about the current and/or future system.

Data Models Fact Finding Techniques

Examining documents (document

review)

Interviewing

Observation the organization in

operationsResearch

Questionnaire 5 commonly used fact finding

techniques

11

Data Models The Evolution of Data Models

Hierarchical Database Model• Represented by a group of records that relates to each

others by a pointer

Network Database Model• Based on set theory, a set consists a collection of records

Relational Database Model• Based on the mathematical concept of relational

Object-Oriented Model• Based on object oriented concepts

12


13

Developed in the 1960s to manage large amounts of data for complex manufacturing projects

Basic logical structure is represented by an upside-down “tree” or by a group of records that relates to each others by a pointer The uppermost record is a Root The lower record in a hierarchy is a Child

Depicts a set of one-to-many (1:M) relationships between a parent and its children segments Each parent can have many children each child has only one parent

Hierachical Database Model


14



15


Abu Johor 3000 Samad Kedah 2500

A001 A002 A003

Nut Washer Hammer Bolt

Root

NutWasher

A004

Zaitun Melaka 4500

Nut


16


Source: http://worldacademyonline.com/article/25/359/data_models__relational__hierarchical_and_network_.html

Root Segme

nt


17

Advantages Many of the hierarchical data model’s features

formed the foundation for current data models Its database application advantages are replicated,

albeit in a different form, in current database environments

Generated a large installed (mainframe) base, created a pool of programmers who developed numerous tried-and-true business applications



18

Develop in 1970 in Conference on Data Systems Languages (CODASYL), by Database Task Group (DBTG)

Created to Represent complex data relationships more

effectively Improve database performance Impose a database standard

Resembles hierarchical model Collection of records in 1:M relationships

Network Database Model


19

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

A parent can have many child records A child can have more than one parent record



20



21


Abu

Samad

Zaitun

Johor

Kedah

Melaka

3000

2500

4500

A001

A002

A003

Nut

Washer

Hammer

BoltA004

CUSTOMER PRODUCTINVOICE


22


Source: http://worldacademyonline.com/article/25/359/data_models__relational__hierarchical_and_network_.html


23

Disadvantages Too cumbersome/difficult to handle The lack of ad hoc query capability put heavy

pressure on programmers Any structural change in the database could

produce havoc in all application programs that drew data from the database

Many database old-timers can recall the interminable information delays



24

Developed by Codd (IBM) in 1970 considered ingenious but impractical in 1970

Conceptually simple, based on mathematical concept of relational

Computers lacked power to implement the relational model Today, microcomputers can run sophisticated relational

database software Relational Database Management System (RDBMS) Performs same basic functions provided by hierarchical and

network DBMS systems, in addition to a host of other functions Most important advantage of the RDBMS is its ability to hide the

complexities of the relational model from the user

Relational Model


25

Relational Model• Matrix consisting of a series of row/column

intersections• Related to each other through sharing a

common entity characteristic

Table (relations)

• Representation of relational database’s entities, attributes within those entities, and relationships between those entities

Relational diagram

• Stores a collection of related entities• Resembles a file

Relational Table

• How data are physically stored in the database is of no concern to the user or the designer

• This property became the source of a real database revolution

Relational table is purely logical structure


26

Example of table structure/relational table

Relational Model


27

Example of table with data/relational table

Relational Model


28

Example of table relationship/relational diagram

Relational Model

Data ModelsThe Evolution of Data Models

29

Example of form

Relational Model


30

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

Relational Model


31

Entity Relationship (E-R) Model Introduced by Chen in 1976 Widely accepted and adapted graphical tool for data

modeling Graphical representation of entities and their

relationships in dB structure Entity Relationship Diagram (ERD)

• Uses graphic representations to model database components

• Entity is mapped to a relational table

Relational Model


32

Example of ERD

Relational Model

Chen

Crow’s

Foot


33

Modeled both data and their relationships in a single structure known as an object

OO data model (OODM) is the basis for the OO database management system (OODBMS)

Object Oriented Model


34

Object described by its factual content equivalent to entity in Relational Model

Includes information about relationships between facts within object, and relationships with other objects but still unlike relational model’s entity

Subsequent OODM development allowed an object to also contain all operations: changing its data values, finding specific data values, printing data values

Object becomes basic building block for autonomous structures



35

Object is an abstraction of a real-world entity E.g. PERSON, VEHICLE

Attributes describe the properties of an object E.g. Name, IC Number, Address

Objects that share similar characteristics are grouped in classes Shared structured (attributes) and behavior (methods)

Classes are organized in a class hierarchy Inheritance is the ability of an object within the class

hierarchy to inherit the attributes and methods of classes above it



36

A comparison of the OO model and the ER model


Data ModelsA Summary

37

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 Representation of real-world transformations

(behavior) must comply with consistency and integrity characteristics of any data model

Data ModelsA Summary: The development of data model

38

Semantic data - data is organized in such a way that it can be interpreted meaningfully without human intervention

Data ModelsDegrees of Data Abstraction

39

Way of classifying data models Many processes begin at high level of abstraction

and proceed to an ever-increasing level of detail Designing a usable database follows the same

basic process The major purpose of a database system is to

provide users with an abstract view of the system.

The system hides certain details of how data is stored and created and maintained

Complexity should be hidden from database users.

Data ModelsDegrees of Data Abstraction

40

American National Standards Institute (ANSI) Standards Planning and Requirements Committee (SPARC)

Defined a framework for data modeling based on degrees of data abstraction (1970s):

The famous “Three Level ANSI-SPARC Architecture”

External

Conceptual

Internal

Data Models Degrees of Data Abstraction

41

Data abstraction levels

Data ModelsThree Level ANSI-SPARC Architecture

42

2. Conceptual level

3. Internal level

Physical data organization

1. External level View 1 View 2 View n

Conceptual Schema

Internal Schema

Database

User nUser 2User 1

…

Conceptual Model

External Model

Internal Model

Physical Model

-designer’s view-h/w independent-s/w independent

-DBMS’s view-h/w independent-s/w dependent

-h/w dependent-s/w dependent

-user’s view

ERD

Three Level ANSI-SPARC ArchitectureExternal Model

43

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

Advantages: 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 Creation of external models helps to ensure security

constraints in the database design Simplifies application program development

Three Level ANSI-SPARC ArchitectureExternal Model

44

Example of External Model for Tiny College

Three Level ANSI-SPARC Architecture Conceptual Model

45

Global view of the entire database concept of the dB Describe what data is stored in the dB and relations among

the data

Data as viewed by the entire organization logical structure

Basis for identification and high-level description of main data objects, avoiding details

Most widely used conceptual model is the entity relationship (ER) model

Provides a relatively easily understood macro level view of data environment

Software and Hardware Independent 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

Three Level ANSI-SPARC Architecture Conceptual Model

46

Example of Conceptual Model for Tiny college

Three Level ANSI-SPARC Architecture Internal Model

47

Representation of the database as “seen” by the DBMS Describes how the data is stored in the dB

Maps the conceptual model to the DBMS Internal schema depicts a specific representation of an internal

model Physical representation of the dB on the computer

Software Dependent and Hardware Independent Depend on the DBMS software used to implement the model Does not depend on the hardware used in the implementation

of the model

Three Level ANSI-SPARC Architecture Internal Model

48

An Internal Model for Tiny College

Three Level ANSI-SPARC Architecture Physical Model

49

The Physical Model

Operates at lowest level of abstraction, describing the way data are saved on storage media such as disks or tapes how the data is stored in the database

Software and Hardware Dependent Requires that database designers have a detailed knowledge of

the hardware and software used to implement database design

Three Level ANSI-SPARC Architecture Physical Model

50

The Physical Model

Summary of Data Models The Evolution of Data Models

51

A data model is a (relatively) simple abstraction of a complex real-world data environment

Basic data modeling components are:i. _____________________ii. _____________________iii. _____________________iv. _____________________

Data modeling requirements are a function of different data views (global vs. local) and level of data abstraction

Summary of Data Models The Evolution of Data Models

Hierarchical Database Model• _________________________________________________

Network Database Model• ________________________________________________

Relational Database Model• _____________________________________________

Object-Oriented Model• _____________________________________________

52

Summary of Data Models Three Level ANSI-SPARC Architecture

53

2. Conceptual level

3. Internal level

Physical data organization

1. External level View 1 View 2 View n

Conceptual Schema

Internal Schema

Database

User nUser 2User 1

…

Internal Model

Physical Model

-designer’s view-h/w independent-s/w independent

-DBMS’s view-h/w independent-s/w dependent

-h/w dependent-s/w dependent

-user’s view

ERD

file systems & database 1.5: data models

Documents

data models fact

end users data models

large amounts of data

techniques11data models

business processesto

business rules10generallynouns

datadata model

captured facts