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Chapter 2 :
  Database
Environment
     Database Systems   1
Learning Outcomes

At the end of this chapter, students will be able to:
    Describe ANSI/SPARC Architecture
    Described roles in database environment
    Describe data models & conceptual modeling




                           Database Systems             2
Objectives of Three-Level Architecture
    All users should be able to access same
     data.

    A user's view is immune to changes made
     in other views.

    Users should not need to know physical
     database storage details.


                      Database Systems         3
Objectives of Three-Level Architecture
     DBA should be able to change database
      storage structures without affecting the
      users' views.
     Internal structure of database should be
      unaffected by changes to physical aspects
      of storage.
     DBA should be able to change conceptual
      structure of database without affecting all
      users.
                         Database Systems           4
ANSI-SPARC Three-Level Architecture




                                    ANSI - American
                                    National Standards
                                    Institute
                                    SPARC - Standards
                                    Planning and
                                    Requirements
                                    Committee




                 Database Systems                    5
ANSI-SPARC Three-Level Architecture
   External Level
     Users’ view of the database.

     Describes that part of database that is relevant to a
       particular user.
   Conceptual Level
     Community view of the database.

     Describes what data is stored in database and
       relationships among the data.
   Internal Level
     Physical representation of the database on the
       computer.
     Describes how the data is stored in the database.

                             Database Systems                 6
Differences between Three Levels of
ANSI-SPARC Architecture




                 Database Systems     7
Data Independence and the ANSI-
SPARC Three-Level Architecture
  Data Independence: structure of
  organization and data format which are
  stored physically in storage are independent
  from its application.

  Specifically, data independence means
  changes in storage structure and data
  access technique does NOT affect
  application program.

                       Database Systems          8
Data Independence and the ANSI-
SPARC Three-Level Architecture




                 Database Systems   9
Data Independence
   Logical Data Independence
     Refers to immunity of external schemas to changes in
      conceptual schema.
     Conceptual schema changes (e.g. addition/removal of
      entities).
     Should not require changes to external schema or
      rewrites of application programs.
   Physical Data Independence
     Refers to immunity of conceptual schema to changes in
      the internal schema.
     Internal schema changes (e.g. using different file
      organizations, storage structures/devices).
     Should not require change to conceptual or external
      schemas.

                            Database Systems                 10
Roles in the Database Environment

   Data Administrator (DA)
   Database Administrator (DBA)
   Database Designers (Logical and Physical)
   Application Programmers
   End Users (naive and sophisticated)




                       Database Systems         11
Database Languages
   Data Definition Language (DDL)
       Allows the DBA or user to describe and name
        entities, attributes, and relationships required
        for the application
       plus any associated integrity and security
        constraints.




                           Database Systems                12
Database Languages
   Data Manipulation Language (DML)
       Provides basic data manipulation operations
        on data held in the database.
   Procedural DML
       allows user to tell system exactly how to
        manipulate data.
   Non-Procedural DML
       allows user to state what data is needed rather
        than how it is to be retrieved.


                           Database Systems               13
Database Languages
   Fourth Generation Language (4GL)
       Query Languages
       Forms Generators
       Report Generators
       Graphics Generators
       Application Generators




                         Database Systems   14
Data Model
   Integrated collection of concepts for
    describing data, relationships between data,
    and constraints on the data in an organization.

   Data Model comprises:
     a structural part;
     a manipulative part;
     possibly a set of integrity rules.


   Purpose
     To represent data in an understandable way.


                           Database Systems           15
Data Models
   Categories of data models include:
     Object-based
     Record-based
     Physical.


   Object-Based Data Models
     Entity-Relationship
     Semantic
     Functional
     Object-Oriented.


                         Database Systems   16
Data Models

   Record-Based Data Models
     Relational Data Model
     Network Data Model
     Hierarchical Data Model.


   Physical Data Models




                      Database Systems   17
Conceptual Modelling
   Conceptual schema is the core of a system supporting
    all user views.

   Should be complete and accurate representation of an
    organization’s data requirements.
   Conceptual modeling is process of developing a
    model of information use that is independent of
    implementation details.

   Result is a conceptual data model.

                            Database Systems               18
Functions of a DBMS
    Data Storage, Retrieval, and Update.

    A User-Accessible Catalog.

    Transaction Support.

    Concurrency Control Services.

    Recovery Services.

                          Database Systems   19
Functions of a DBMS
    Authorization Services.

    Support for Data Communication.

    Integrity Services.

    Services to Promote Data Independence.

    Utility Services.


                           Database Systems   20
Components of a DBMS




                Database Systems   21
Components of Database Manager (DM)




                  Database Systems    22
END OF CHAPTER 2
        Database Systems   23

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Chapter 2 database environment

  • 1. Chapter 2 : Database Environment Database Systems 1
  • 2. Learning Outcomes At the end of this chapter, students will be able to:  Describe ANSI/SPARC Architecture  Described roles in database environment  Describe data models & conceptual modeling Database Systems 2
  • 3. Objectives of Three-Level Architecture  All users should be able to access same data.  A user's view is immune to changes made in other views.  Users should not need to know physical database storage details. Database Systems 3
  • 4. Objectives of Three-Level Architecture  DBA should be able to change database storage structures without affecting the users' views.  Internal structure of database should be unaffected by changes to physical aspects of storage.  DBA should be able to change conceptual structure of database without affecting all users. Database Systems 4
  • 5. ANSI-SPARC Three-Level Architecture ANSI - American National Standards Institute SPARC - Standards Planning and Requirements Committee Database Systems 5
  • 6. ANSI-SPARC Three-Level Architecture  External Level  Users’ view of the database.  Describes that part of database that is relevant to a particular user.  Conceptual Level  Community view of the database.  Describes what data is stored in database and relationships among the data.  Internal Level  Physical representation of the database on the computer.  Describes how the data is stored in the database. Database Systems 6
  • 7. Differences between Three Levels of ANSI-SPARC Architecture Database Systems 7
  • 8. Data Independence and the ANSI- SPARC Three-Level Architecture Data Independence: structure of organization and data format which are stored physically in storage are independent from its application. Specifically, data independence means changes in storage structure and data access technique does NOT affect application program. Database Systems 8
  • 9. Data Independence and the ANSI- SPARC Three-Level Architecture Database Systems 9
  • 10. Data Independence  Logical Data Independence  Refers to immunity of external schemas to changes in conceptual schema.  Conceptual schema changes (e.g. addition/removal of entities).  Should not require changes to external schema or rewrites of application programs.  Physical Data Independence  Refers to immunity of conceptual schema to changes in the internal schema.  Internal schema changes (e.g. using different file organizations, storage structures/devices).  Should not require change to conceptual or external schemas. Database Systems 10
  • 11. Roles in the Database Environment  Data Administrator (DA)  Database Administrator (DBA)  Database Designers (Logical and Physical)  Application Programmers  End Users (naive and sophisticated) Database Systems 11
  • 12. Database Languages  Data Definition Language (DDL)  Allows the DBA or user to describe and name entities, attributes, and relationships required for the application  plus any associated integrity and security constraints. Database Systems 12
  • 13. Database Languages  Data Manipulation Language (DML)  Provides basic data manipulation operations on data held in the database.  Procedural DML  allows user to tell system exactly how to manipulate data.  Non-Procedural DML  allows user to state what data is needed rather than how it is to be retrieved. Database Systems 13
  • 14. Database Languages  Fourth Generation Language (4GL)  Query Languages  Forms Generators  Report Generators  Graphics Generators  Application Generators Database Systems 14
  • 15. Data Model  Integrated collection of concepts for describing data, relationships between data, and constraints on the data in an organization.  Data Model comprises:  a structural part;  a manipulative part;  possibly a set of integrity rules.  Purpose  To represent data in an understandable way. Database Systems 15
  • 16. Data Models  Categories of data models include:  Object-based  Record-based  Physical.  Object-Based Data Models  Entity-Relationship  Semantic  Functional  Object-Oriented. Database Systems 16
  • 17. Data Models  Record-Based Data Models  Relational Data Model  Network Data Model  Hierarchical Data Model.  Physical Data Models Database Systems 17
  • 18. Conceptual Modelling  Conceptual schema is the core of a system supporting all user views.  Should be complete and accurate representation of an organization’s data requirements.  Conceptual modeling is process of developing a model of information use that is independent of implementation details.  Result is a conceptual data model. Database Systems 18
  • 19. Functions of a DBMS  Data Storage, Retrieval, and Update.  A User-Accessible Catalog.  Transaction Support.  Concurrency Control Services.  Recovery Services. Database Systems 19
  • 20. Functions of a DBMS  Authorization Services.  Support for Data Communication.  Integrity Services.  Services to Promote Data Independence.  Utility Services. Database Systems 20
  • 21. Components of a DBMS Database Systems 21
  • 22. Components of Database Manager (DM) Database Systems 22
  • 23. END OF CHAPTER 2 Database Systems 23