RDBMS Concepts - PowerPoint by HZPSpuY5

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									•   RDBMS Concepts
    Introduction
    Database Management Systems
    Normalization
                             Introduction

                        Data Storage Methods
•   Data is represented in one or more flat files
•   Flat file is nothing but electronic representation of cardboard file.
•   Every business group has its own set of files
              Disadvantages of Flat File Systems
•   No centralized control.
•   Data Redundancy
•   Data Inconsistency
•   Data can not be shared
•   Standards can not be enforced
•   Security issues
•   Integrity can not be maintained
•   Data dependence
              Database Management Systems

•   A system whose overall purpose is to record and maintain information
•   A database is a repository for stored data and programs to manipulate it.
                          Advantages of DBMS

•   Centralized control.
•   No Data Redundancy
•   Data Consistency
•   Data can be shared
•   Standards can be enforced
•   Security can be enforced
•   Integrity can be maintained
•   Data independence
                     Data Models

• A data model is a collection of concepts for describing
  data
• A Schema is a description of a particular collection of
  data using the given data model
• The relational model is the most widely used model
  today
          Levels of Abstraction
• Many Views and single
  Conceptual and Physical
  Schema
• Views Describe how users
  see the data
• Conceptual Schema defines
  the logical structure
• Physical Schema defines the
  physical files and Indexes
          Data Independence
• Applications insulated from how data is
  structured and stored
• Logical Data Independence: Protection from
  changes in logical structure of data
• Physical Data Independence: Protection from
  changes in physical structure of data
Structure of a DBMS
                 Types of DBMS
• Hierarchical

• Network

• Relational
            Hierarchical DBMS
• Data is represented by a tree structure
• Can not handle Many-Many relations

• Can not reflect all real life situations

• Anomalies in insert, delete and update
  operations
               Network DBMS
•   Data is represented by records and pointers
•   Addresses Many-Many relations
•   Insert,delete,update operations possible
•   Complex in design
                 Relational DBMS

• Based on Relational Mathematics principles
• Data is represented in terms of rows and columns of a
  table
• Addresses all types of relations
• Easy to design
• No anomalies for insert/delete/update
               Normalization
• Normalization - process of removing data
  redundancy by decomposing relations in a
  Database.

• De normalization - carefully introduced redundancy
  to improve query performance.
• The decomposition approach starts with one relation
  and the relation is decomposed into more number of
  relations to remove insert, delete and update
  anomalies.

• 1NF, 2NF, 3NF and BCNF can be achieved by this
  approach.
           Un normalized Form
• A relation is said to be in   S#   PQ
  Un normalized Form                 P#   QTY
  (0NF) if the values of any    S1   P1   300
  of its attributes are non-         P2
                                     P3
                                          200
                                          400
  atomic. In other words             P4   200
  more than one value is        S2   P1   300
  associated with each               P2   400

  instance of the attribute.    S3   P2   200
                 First Normal Form
• A Relation is said to be in First Normal Form (1 NF) if the
  values of each attribute of the relation are atomic. In other
  words, only one value is associated with each attribute and
  the value is not a set or a list of values.
                  Functional Dependency
 Given a relation R, attribute Y of R is functionally dependent on
 attribute X if and only if each X-value in R has associated with it
            precisely one Y-value in R (at any one time)
                  Full Functional Dependency
    Attribute Y is fully functionally dependent on attribute X if it is
   functionally dependent on X And Functionally dependent on any
                            proper subset of X
                   Second Normal Form

• A relation R is in Second Normal Form (2 NF) if it is in the 1NF and
  every non key attribute is full functionally dependent on the primary
  key.
                         Third Normal Form
• A relation R is in Third Normal Form (3 NF) if and only if it is in the
  2NF and every non-key attribute is
  non-transitively dependent on the primary key.
                     Boyce Codd Normal Form
A relation R is in Boyce/Codd Normal Form (BCNF) if and only if every
   determinant is a candidate key.

An attribute, possibly composite, on which some other attribute is fully
  functionally dependent is a determinant

								
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