KEMBAR78
data modeling and models | PPT
Data Modeling &Data Modeling &
Data ModelsData Models
Group no. 1
15171511-016
15171511-012
Presentation topic:
Objectives:Objectives:
What is data modeling?
What is data model?
Importance of data models.
Data Models basic building blocks.
Evolution of data models.
Advantages of data models.
& disadvantages of data models.
2
Data Modeling:Data Modeling:
Data modeling is often the first step in database
design and object-oriented programming as the
designers first create a conceptual model of
how data items relate to each other. Data
modeling involves a progression from
conceptual model to logical model to physical
schema.
3
What is Data Model?What is Data Model?
 Data Model is a collection of conceptual tools for describing data,
data relationships, data semantics and consistency constraint.
 A data model is a conceptual representation of data structures
required for data base and is very powerful in expressing and
communicating the business requirements.
 A data model visually represents the nature of data, business rules
governing the data, and how it will be organized in the database.
4
The Importance of 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.
5
The Importance of Data ModelsThe Importance of Data Models
(continued)(continued)
End-users have different views and needs for data.
Data model organizes data for various users.
6
7
Data Model Basic BuildingData Model Basic Building
BlocksBlocks
Entity - anything about which data are to be collected and
stored
Attribute - a characteristic of an entity
Relationship - describes an association among 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
8
The Evolution of Data ModelsThe Evolution of Data Models
Hierarchical
Network
Relational
Entity relationship
Object oriented (OO)
9
The Hierarchical ModelThe 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”
10
The Hierarchical ModelThe Hierarchical Model
(continued)(continued)
11
The Hierarchical ModelThe Hierarchical Model
(continued)(continued)
The hierarchical structure contains levels,
or segments
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
12
The Hierarchical ModelThe Hierarchical Model
(continued)(continued)
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
13
The Hierarchical ModelThe Hierarchical Model
(continued)(continued)
Disadvantages
◦ Complex to implement
◦ Difficult to manage
◦ Lacks structural independence
◦ Implementation limitations
◦ Lack of standards
14
The Network ModelThe Network Model
Created to
◦ Represent complex data relationships more
effectively
◦ Improve database performance
◦ Impose a database standard
Conference on Data Systems
Languages (CODASYL)
Database Task Group (DBTG)
15
The Network Model (continued)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
Data Management Language (DML)
◦ Defines the environment in which data can be
managed
16
The Network Model (continued)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
DML
◦ Works with the data in the database
17
The Network Model (continued)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
18
The Network Model (continued)The Network Model (continued)
19
The Network Model (continued)The Network Model (continued)
Disadvantages
◦ Too cumbersome
◦ 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
20
The Relational ModelThe Relational Model
Developed by Codd (IBM) in 1970.
Considered ingenious but impractical in
1970.
Conceptually simple.
Computers lacked power to implement the
relational model.
Today, microcomputers can run
sophisticated relational database software.
21
The Relational Model (continued)The Relational Model (continued)
Table (relations)
◦ Matrix consisting of a series of row/column
intersections
◦ Related to each other through sharing a
common entity characteristic
Relational diagram
◦ Representation of relational database’s entities,
attributes within those entities, and
relationships between those entities
22
The Relational ModelThe Relational Model
(continued)(continued)
Relational Table
◦ Stores a collection of related entities
 Resembles a file
Relational table is purely logical
structure
◦ 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
23
The Relational Model (continued)The Relational Model (continued)
24
The Relational Model (continued)The Relational Model (continued)
25
The Relational Model (advantages)The Relational Model (advantages)
Structural independence.
Improved conceptual simplicity.
Easier database design,
implementation, management, and use.
Ad hoc query capability.
Powerful database management
system.
26
The Relational ModelThe Relational Model
(disadvantages)(disadvantages)
Substantial hardware and system
software overhead
Can facilitate poor design and
implementation
May promote “islands of information”
problems
27
The Entity Relationship ModelThe 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
28
The Entity Relationship ModelThe Entity Relationship Model
(continued)(continued)
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
table
Entity set is collection of like entities
Connectivity labels types of relationships
◦ Diamond connected to related entities
through a relationship line
29
The Entity Relationship ModelThe Entity Relationship Model
(continued)(continued)
30
The Entity RelationshipThe Entity Relationship
Model (continued)Model (continued)
31
The Object Oriented ModelThe Object Oriented Model
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
32
The Object Oriented ModelThe Object Oriented Model
(continued)(continued)
Object described by its factual content
◦ Like relational model’s entity
Includes information about relationships
between facts within object, and
relationships with other objects
◦ Unlike relational model’s entity
Subsequent OODM development allowed
an object to also contain all operations
Object becomes basic building block for
autonomous structures
33
The Object Oriented ModelThe Object Oriented Model
(continued)(continued)
Object is an abstraction of a real-world
entity
Attributes describe the properties of an
object
Objects that share similar characteristics
are grouped in classes
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
34
The Object Oriented ModelThe Object Oriented Model
(continued)(continued)
35
Data Models: A SummaryData 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
◦ Representation of real-world transformations
(behavior) must comply with consistency and
integrity characteristics of any data model
36
Data Models: A SummaryData Models: A Summary
(continued)(continued)
37

data modeling and models

  • 1.
    Data Modeling &DataModeling & Data ModelsData Models Group no. 1 15171511-016 15171511-012 Presentation topic:
  • 2.
    Objectives:Objectives: What is datamodeling? What is data model? Importance of data models. Data Models basic building blocks. Evolution of data models. Advantages of data models. & disadvantages of data models. 2
  • 3.
    Data Modeling:Data Modeling: Datamodeling is often the first step in database design and object-oriented programming as the designers first create a conceptual model of how data items relate to each other. Data modeling involves a progression from conceptual model to logical model to physical schema. 3
  • 4.
    What is DataModel?What is Data Model?  Data Model is a collection of conceptual tools for describing data, data relationships, data semantics and consistency constraint.  A data model is a conceptual representation of data structures required for data base and is very powerful in expressing and communicating the business requirements.  A data model visually represents the nature of data, business rules governing the data, and how it will be organized in the database. 4
  • 5.
    The Importance ofData 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. 5
  • 6.
    The Importance ofData ModelsThe Importance of Data Models (continued)(continued) End-users have different views and needs for data. Data model organizes data for various users. 6
  • 7.
  • 8.
    Data Model BasicBuildingData Model Basic Building BlocksBlocks Entity - anything about which data are to be collected and stored Attribute - a characteristic of an entity Relationship - describes an association among 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 8
  • 9.
    The Evolution ofData ModelsThe Evolution of Data Models Hierarchical Network Relational Entity relationship Object oriented (OO) 9
  • 10.
    The Hierarchical ModelTheHierarchical 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” 10
  • 11.
    The Hierarchical ModelTheHierarchical Model (continued)(continued) 11
  • 12.
    The Hierarchical ModelTheHierarchical Model (continued)(continued) The hierarchical structure contains levels, or segments 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 12
  • 13.
    The Hierarchical ModelTheHierarchical Model (continued)(continued) 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 13
  • 14.
    The Hierarchical ModelTheHierarchical Model (continued)(continued) Disadvantages ◦ Complex to implement ◦ Difficult to manage ◦ Lacks structural independence ◦ Implementation limitations ◦ Lack of standards 14
  • 15.
    The Network ModelTheNetwork Model Created to ◦ Represent complex data relationships more effectively ◦ Improve database performance ◦ Impose a database standard Conference on Data Systems Languages (CODASYL) Database Task Group (DBTG) 15
  • 16.
    The Network Model(continued)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 Data Management Language (DML) ◦ Defines the environment in which data can be managed 16
  • 17.
    The Network Model(continued)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 DML ◦ Works with the data in the database 17
  • 18.
    The Network Model(continued)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 18
  • 19.
    The Network Model(continued)The Network Model (continued) 19
  • 20.
    The Network Model(continued)The Network Model (continued) Disadvantages ◦ Too cumbersome ◦ 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 20
  • 21.
    The Relational ModelTheRelational Model Developed by Codd (IBM) in 1970. Considered ingenious but impractical in 1970. Conceptually simple. Computers lacked power to implement the relational model. Today, microcomputers can run sophisticated relational database software. 21
  • 22.
    The Relational Model(continued)The Relational Model (continued) Table (relations) ◦ Matrix consisting of a series of row/column intersections ◦ Related to each other through sharing a common entity characteristic Relational diagram ◦ Representation of relational database’s entities, attributes within those entities, and relationships between those entities 22
  • 23.
    The Relational ModelTheRelational Model (continued)(continued) Relational Table ◦ Stores a collection of related entities  Resembles a file Relational table is purely logical structure ◦ 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 23
  • 24.
    The Relational Model(continued)The Relational Model (continued) 24
  • 25.
    The Relational Model(continued)The Relational Model (continued) 25
  • 26.
    The Relational Model(advantages)The Relational Model (advantages) Structural independence. Improved conceptual simplicity. Easier database design, implementation, management, and use. Ad hoc query capability. Powerful database management system. 26
  • 27.
    The Relational ModelTheRelational Model (disadvantages)(disadvantages) Substantial hardware and system software overhead Can facilitate poor design and implementation May promote “islands of information” problems 27
  • 28.
    The Entity RelationshipModelThe 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 28
  • 29.
    The Entity RelationshipModelThe Entity Relationship Model (continued)(continued) 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 table Entity set is collection of like entities Connectivity labels types of relationships ◦ Diamond connected to related entities through a relationship line 29
  • 30.
    The Entity RelationshipModelThe Entity Relationship Model (continued)(continued) 30
  • 31.
    The Entity RelationshipTheEntity Relationship Model (continued)Model (continued) 31
  • 32.
    The Object OrientedModelThe Object Oriented Model 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 32
  • 33.
    The Object OrientedModelThe Object Oriented Model (continued)(continued) Object described by its factual content ◦ Like relational model’s entity Includes information about relationships between facts within object, and relationships with other objects ◦ Unlike relational model’s entity Subsequent OODM development allowed an object to also contain all operations Object becomes basic building block for autonomous structures 33
  • 34.
    The Object OrientedModelThe Object Oriented Model (continued)(continued) Object is an abstraction of a real-world entity Attributes describe the properties of an object Objects that share similar characteristics are grouped in classes 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 34
  • 35.
    The Object OrientedModelThe Object Oriented Model (continued)(continued) 35
  • 36.
    Data Models: ASummaryData 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 ◦ Representation of real-world transformations (behavior) must comply with consistency and integrity characteristics of any data model 36
  • 37.
    Data Models: ASummaryData Models: A Summary (continued)(continued) 37