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Database 3   Conceptual Modeling And Er
 

Database 3 Conceptual Modeling And Er

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    Database 3   Conceptual Modeling And Er Database 3 Conceptual Modeling And Er Presentation Transcript

      • In previous section
        • General steps in DB development process , ISA ,EDM
        • Database Architectures
      • Aim
      • Design of conceptual Data Model
      • Objectives
      • Understand
        • Conceptual Data Modeling
        • Concepts of E-R Modeling
        • Model Example & Limitations
      RECAP
      • Purpose:
        • create detailed specification of internal documents and tasks from the EDM
      • Input:
        • EDM, usage statistics, and other information gathered during the analysis
      • Output:
        • ER-Diagram, Data Representation, Constraints, Task Decompositions
      • Techniques:
        • data modeling
        • top-down decomposition of tasks until their specification is sufficiently detailed to allow a programmer to implement them
        • task decomposition may result in tasks replacing the original task or in subtasks controlled by the original task
      • Tools: ER-Model
      APPROACH
      • To build a
      • What is 1 st Step ?
      • What are the choices,Why ?
      • User Requirements
      • - User is not sure
      • - Precise specification is difficult
      • Communication Problems
      • - Analyst & user communication
      • - User not willing to take responsibility
      • Technical
        • - Skills of modeler
        • - Design Methodology – Non Standard
      CONCEPTUAL MODEL
    • Feasibility study Requirement Analysis & Specifications Data Modeling Process Modeling Implementation Prototyping Testing DESIGN APPROACH
    • DESIGN PHASES Requirements Collection & Analysis Conceptual Design (G) Logical Design (Blue Print) Physical Design Application Design Methods Req. Collection Conceptual Model Data Base System DBMS Tools , OS Requirements Specs Conceptual Database Model Logical Models Performance Tests Final Schema Application PGMS
    • Conceptual Design Logical Design Physical Design Application Design Requirement Collection & Analysis C,Windows,Power Builder ORACLE Relational DBs ER & ERR Model Questionnaire & Interview DESIGN METHODS
      • Models can be useful when we want to examine or manage part of the real world
      • The costs of using a model are often considerably lower than the costs of using or experimenting with the real world itself
      • Examples:
        • airplane simulator
        • nuclear power plant simulator
        • flood warning system
        • model of US economy
        • model of a heat reservoir
        • map
      WHY TO USE MODEL
    • A Map Is a Model of Reality MODEL OF REALITY
      • A model is a means of communication
      • Users of a model must have a certain amount of knowledge in common
      • A model on emphasized selected aspects
      • A model is described in some language
      • A model can be erroneous
      • A message to map makers: “Highways are not painted red, rivers don’t have county lines running down the middle, and you can’t see contour lines on a mountain” [Kent 78]
      MODEL TO RAISE QUESTION
        • A process that construct an abstract model which represents the entities,relationships and activities of an enterprise of real world
        • Putting a Real World Object on to Paper
      Purpose of model is to sharpen the question MYCOM.COM    US $ 10 b
      MCA/MMS IIPS CONCEPTUAL MODELING
      • Why Conceptual Modeling ?
      • Obtain better understanding of business
      • Enable the end-user communication
      • Discover design errors at early stage
      • Build a Solid Foundation
      • Ensure the quality
      • A DBMS independent DB design
      • What to Model ?
      • Static information
        • Data - Entities
        • Associations - Relationship among entities
      • Dynamic Information
        • Process – operations/transactions
        • Integrity constraints – Business Rules / Regulations
      CONCEPTUAL MODELING
      • Process - Oriented Approach
        • Focus on activities, process & operations
        • Data Flow Diagram
      • Data – Oriented Approach
        • Focus on data & their relationship
        • Characteristics of Data captured
        • Data more complex than process
        • Rich data source is the GOAL
        • Data is more stable than process
        • Data Orientation - Longer life
      • Object – Oriented Approach
        • Combine data and process
      CONCEPTUAL MODELING APPROACHES
      • Entity – relationship model (ER) introduced in 1976 by Peter Chen
      • Extended ER model (EER) expanded the original ER with new concepts
      ER MODELING
      • Entity
      • An Entity is a conceptual object
      • Physically or conceptually exists
      • Usually a noun in requirement specification
        • E.g. Lecturer , Course , Movie , Sales-order
      Lecturer Course SSN Name Teach
      • Collection of Entities have same properties
      • An entity instance is a single occurrence of entity type
      • Described once in metadata
      • A noun in requirement specifications
      • A true data entity have many instances,each with distinguishing feature
      • A strong entity – exists independently like student , Course , Car
      • A weak entity – existence depends upon other entity (identifying owner)
      • Dependent
      ENTITY TYPES
      • Property , description of entities and entity types
      • Attribute type ( domain)
        • Define all possible attribute values
      • Attribute value , associated with individual entities
      • A noun or an objective in requirement specifications
      IM-99-02 Student ID DoB  Singh 4-9-77
      • Entities – Attributes
      • Entities have ‘independent’ meaning e.g. Car , Student
      • Attributes have no independent meaning
      ? ID ATTRIBUTE
      • Uniquely identify individual instances of an entity type
        • A key refers to one or a group of attributes as a whole
        • A key attribute refers to a component of a composite key
        • Definition of a key changes with Data Semantics
      • An entity type may have few keys
        • Primary key – One of candidate key
        • Secondary key – Other keys
      • The primary key attribute (s) underlined
      • Choose key – will not change
      • Choose key – Not Null
      • Avoid INTELLIGENT KEYS
      KEY ATTRIBUTE
      • Simple attribute
        • Can’t be broken into smaller values
        • Contains only atomic values
      • Composite attribute
        • Has component attribute
      • Single valued attribute
        • One only per attribute
      • Multi – Valued attribute
        • Contains multiple values
      ATTRIBUTE CLASSIFICATION
    • Student Roll No Skill Dob F.Name M.Name L.Name Name EXAMPLE Degree
      • It is an association among instances of one or more entities involved.
        • Label as
        • Verb in requirement specifications,in present tense & descriptive
        • Example
        • Model associations, not actions and process
      RELATIONSHIP Student Course Faculty Teach take advise
      • How is an entity linked to relationship ? [Participation]
      • How many relationship instances is an entity permitted to be linked to ? [cardinality]
      • Relationship instance is an association between entity instances, where each instance includes exactly one entity from each participating entity type
      JUSTIFICATION Student Advise Faculty       Akr Trupti Kris Ram Mohan Singh
    • E 1 E 2 R min,max min,max Participation 0 – Partial 1 - Total Cardinality 1 - - One M - - More than One O - - One Student CARDINALITY AND PARTICIPATION Advise Faculty X Z Y A B C D
    • Unary Relationship Binary Relationship Ternary/N-ary Relationship RELATIONSHIP DEGREES
    • Person Married (0,1) (0,1) Unary Relationship RELATIONSHIP DEGREE Employee Manager (0,m) (0,1)
    • One –to-one binary Relationship A A One –to-Many binary Relationship B C D X Y Z E1 E2 (1, 1) (0, m) BINARY RELATIONSHIP B C D X Y Z
    • Many to Many binary Relationship X Y Z A B C D BINARY RELATIONSHIP Justification E1 E2 R1 (0, m) (1, m)
    • Customer SELL Salesman Car TERNARY RELATIONSHIP CAR REP (0,1) (0, m) Sell Customer (0,M)
    • Unary n-ary to RELATIONSHIP DEGREE
      • Relationship attributes
      • Attributes describing relationship, like when ,where, what
      Faculty Student Advise Memo Time Date
      • A relationship instance must include all participants
      • Need to be careful when converted to binary relationship
      RELATIONSHIP ATTRIBUTES
      • Attributes on a relationship might suggest to convert it to entity , termed (---) as associative entity.
      Course EMP Completes Date m m CERT Date Number ASSOCIATIVE ENTITY
      • Conditions
        • Result entity independent meaning
        • Result entity participates in one or more other relationships
      Other Notations Mandatory One Mandatory Many Optional One Optional Many CONDITIONS AND NOTATIONS
    • BASIC E-R NOTATION
    • SAMPLE ER DIAGRAM
      • Conceptual Modeling – important skill
      • Conceptual Schema important design document – independent of DBMS
      • Entities , types
      • Relationships Unary – n-ary
      • Associations
        • Cardinality (Connectivity)
        • Participation (Degree)
      SUMMARY