file systems database 1 5 data models n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
FILE SYSTEMS & DATABASE 1.5: Data Models PowerPoint Presentation
Download Presentation
FILE SYSTEMS & DATABASE 1.5: Data Models

Loading in 2 Seconds...

play fullscreen
1 / 53

FILE SYSTEMS & DATABASE 1.5: Data Models - PowerPoint PPT Presentation


  • 170 Views
  • Uploaded on

DB2. ITS232 Introduction To Database. Oracle. MySQL. MS Access. FILE SYSTEMS & DATABASE 1.5: Data Models. Chapter 1. Data Models The Importance of Data Models. Data models Relatively simple representations, usually graphical, of complex real-world data structures

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'FILE SYSTEMS & DATABASE 1.5: Data Models' - willa


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
file systems database 1 5 data models

DB2

ITS232Introduction To Database

Oracle

MySQL

MS Access

FILE SYSTEMS & DATABASE

1.5: Data Models

Chapter 1

data models the importance of data models
Data ModelsThe Importance of Data Models

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 blocks1
Data Models Data Model Basic Building Blocks
  • Based on previous IBM DB2 lab, determine:
data models business rules
Data Models Business Rules
  • 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 rules1
Data Models Business Rules
  • 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:
data models discovering business rules
Data Models Discovering Business Rules

Sources of Business Rules:

  • Company managers
  • Policy makers
  • Department managers
  • Written documentation
    • Procedures
    • Standards
    • Operations manuals
  • Direct interviews with end users
data models translating business rules into data model components
Data Models Translating Business Rules into Data Model Components
  • 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
data models discovering business rules2
Data Models Discovering Business Rules
  • 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
Data Models Fact Finding Techniques

5 commonly used fact finding techniques

data models the evolution of data models1

Hierachical Database Model

Data Models The Evolution of Data Models
  • 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
data models the evolution of data models3

Abu

Johor

3000

Samad

Kedah

2500

Zaitun

Melaka

4500

  • Hierachical Database Model
Data Models The Evolution of Data Models

Root

A001

A002

A003

A004

Nut

Washer

Washer

Hammer

Nut

Bolt

Nut

data models the evolution of data models4

Hierachical Database Model

Data Models The Evolution of Data Models

Root Segment

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

data models the evolution of data models5

Hierachical Database Model

Data Models The Evolution of Data Models
  • 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
data models the evolution of data models6
Data Models The Evolution of Data Models
  • Network Database Model
  • 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
data models the evolution of data models7
Data Models The Evolution of Data Models
  • Network Database Model
  • 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
data models the evolution of data models9

Abu

Johor

3000

Samad

Kedah

2500

Zaitun

Melaka

4500

Data Models The Evolution of Data Models
  • Network Database Model

CUSTOMER

INVOICE

PRODUCT

A001

Nut

Washer

A002

A003

Hammer

A004

Bolt

data models the evolution of data models10
Data Models The Evolution of Data Models
  • Network Database Model

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

data models the evolution of data models11
Data Models The Evolution of Data Models
  • Network Database Model
  • 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
data models the evolution of data models12
Data Models The Evolution of Data Models
  • Relational Model
  • 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
data models the evolution of data models14
Data Models The Evolution of Data Models
  • Relational Model
  • Example of table structure/relational table
data models the evolution of data models15
Data Models The Evolution of Data Models
  • Relational Model
  • Example of table with data/relational table
data models the evolution of data models16
Data Models The Evolution of Data Models
  • Relational Model
  • Example of table relationship/relational diagram
data models the evolution of data models17
Data ModelsThe Evolution of Data Models
  • Relational Model
  • Example of form
data models the evolution of data models18
Data ModelsThe Evolution of Data Models
  • Relational Model
  • 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
data models the evolution of data models19
Data ModelsThe Evolution of Data Models
  • Relational Model
  • 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
data models the evolution of data models20
Data ModelsThe Evolution of Data Models
  • Relational Model
  • Example of ERD

Chen

Crow’s Foot

data models the evolution of data models21
Data ModelsThe Evolution of Data Models
  • Object Oriented Model
  • 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)
data models the evolution of data models22
Data ModelsThe Evolution of Data Models
  • Object Oriented Model
  • 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
data models the evolution of data models23
Data Models The Evolution of Data Models
  • Object Oriented Model
  • 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
data models the evolution of data models24
Data Models The Evolution of Data Models
  • Object Oriented Model
  • A comparison of the OO model and the ER model
data models a summary
Data ModelsA 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
    • Representation of real-world transformations (behavior) must comply with consistency and integrity characteristics of any data model
data models a summary the development of data model
Data ModelsA Summary: The development of data model

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

data models degrees of data abstraction
Data ModelsDegrees of Data Abstraction
  • 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 models degrees of data abstraction1
Data ModelsDegrees of Data Abstraction
  • 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”
data models three level ansi sparc architecture
Data ModelsThree Level ANSI-SPARC Architecture

User 2

User 1

User n

-user’s view

External Model

View 1

View 2

View n

1. External level

ERD

-designer’s view

-h/w independent

-s/w independent

Conceptual Model

Conceptual Schema

2. Conceptual level

-DBMS’s view

-h/w independent

-s/w dependent

Internal Schema

Internal Model

3. Internal level

Database

-h/w dependent

-s/w dependent

Physical Model

Physical data

organization

three level ansi sparc architecture external model
Three Level ANSI-SPARC ArchitectureExternal 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

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 architecture external model1
Three Level ANSI-SPARC ArchitectureExternal Model
  • Example of External Model for Tiny College
three level ansi sparc architecture conceptual model
Three Level ANSI-SPARC Architecture Conceptual Model
  • 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 model1
Three Level ANSI-SPARC Architecture Conceptual Model
  • Example of Conceptual Model for Tiny college
three level ansi sparc architecture internal model
Three Level ANSI-SPARC Architecture Internal Model
  • 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 model1
Three Level ANSI-SPARC Architecture Internal Model
  • An Internal Model for Tiny College
three level ansi sparc architecture physical model
Three Level ANSI-SPARC Architecture Physical Model

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
summary of data models the evolution of data models
Summary of Data Models The Evolution of Data Models
  • A data model is a (relatively) simple abstraction of a complex real-world data environment
  • Basic data modeling components are:
    • _____________________
    • _____________________
    • _____________________
    • _____________________
  • Data modeling requirements are a function of different data views (global vs. local) and level of data abstraction
summary of data models three level ansi sparc architecture
Summary of Data Models Three Level ANSI-SPARC Architecture

User 2

User 1

User n

-user’s view

View 1

View 2

View n

1. External level

-designer’s view

-h/w independent

-s/w independent

ERD

Conceptual Schema

2. Conceptual level

-DBMS’s view

-h/w independent

-s/w dependent

Internal Schema

Internal Model

3. Internal level

Database

-h/w dependent

-s/w dependent

Physical Model

Physical data

organization