Lecture3 by taminulislam


									Database Management Systems

           Lecture 3

                       Md. Ahsan- Ul- Hasan
Database Management Systems
   File Organization:
        Bit (represents the smallest unit of data a computer can
        Byte (a group of bits, represents a single character).
        Field (a group of characters, words)
        Record (a group of related fields)
        File (a group of records of the same types)
        Database ( a group of related files)
    Database Management Systems
          Organizing Data in Traditional File Environment
               In most organizations, data files and systems tended to grow
                independently without a company-wide plan. Accounting,
                Finance, Manufacturing, Human resources and Sales and
                Marketing all developed their own systems and data.

Accounting                                                   Files

 Finance                                                     Files
Database Management Systems
   Problems with the traditional file environment:

          Data Redundancy and Inconsistency
          Program-data dependence
          Lack of flexibility
          Poor Security
          Lack of data sharing and availability
         Problems with the traditional file

Data Redundancy and Inconsistency:
                 The presence of duplicate data in multiple data files so that the
                 same data are stored in more than one place or location. Data
                 redundancy occurs when different groups in organization
                 independently collect the same piece of data and store it
                 independently of each other.

Program-Data Dependence:
                 Refers to the coupling of data stored in files and the specific
                 programs required to update and maintain those files such
                 that changes in programs require changes to the data.
       Problems with the traditional file
Lack of Flexibility:
         A traditional files system can deliver routine scheduled reports after
         extensive programming efforts, but it cannot deliver ad hoc reports or
         respond to unanticipated information requirements in a times fashion.

Poor Security:
        There is very little control over file so management may have no way of
        knowing who is accessing or even making changes to the organization’s

Lack of Data sharing and availability
        Pieces of information in different files and different parts of the
        organization cannot be related to one another, it is virtually impossible
        for information to be shared or accessed in a timely manner. Information
        cannot flow freely across different functional areas.
Database Management Systems
Database is a collection of data organized to serve many applications
efficiently by centralizing the data and controlling redundant data.

Database Management Systems (DBMS) is software that permits
organization to centralize data, manage then efficiently, and provide
to the stored data by application programs. The DBMS acts as an
between application programs and the physical data files.
       Database Management Systems


User       SQL     DBMS

Database Management Systems
   Relational Database Systems
         Relational database represent data as two-dimensional
Database Management Systems
   Object-Oriented DBMS:
    ◦ An Object Oriented DBMS stores the data and procedures that
      act on those data as objects that can be automatically retrieved
      and shared.

 Distributed database:
  ◦ A distributed database is one that is stored in more than one
    physical location.
 Data warehouse:
  ◦ A data warehouse is a database that stores current and historic
    data of potential interest to decision makers throughout the
    company. Data warehouse provides analytical tools, query tools,
    graphical report facilities.
Database Systems Management
   Data Mining:
       Data mining is the process of extracting patterns from data. Data
        mining is becoming an increasingly important tool to transform these
        data into information. It is commonly used in a wide range of profiling
        practices, such as marketing, surveillance, fraud detection and
        scientific discovery
Data Mining

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