Introduction to Database Systems

We’ll cover the following

  • Introduction
  • Database Management System
  • OS File System Storage Based Approach
  • DBMS Approach
  • Data Model
  • E/R (Entity/Relationship) Model


What is a Database?

A collection of related pieces of data:

  • Representing/capturing the information about a real-world enterprise or part of an enterprise.
  • Collected and maintained to serve specific data management needs of the enterprise.
  • Activities of the enterprise are supported by the database and continually update the database.

An Example

University Database:

Data about students, faculty, courses, research-laboratories, course registration/enrollment etc.
Reflects the state of affairs of the academic aspects of the university.
Purpose: To keep an accurate track of the academic activities of the university.

Database Management System (DBMS)

A general purpose software system enabling:

  • Creation of large disk-resident databases.
  • Posing of data retrieval queries in a standard manner.
  • Retrieval of query results efficiently.
  • Concurrent use of the system by a large number of users in a consistent manner.
  • Guaranteed availability of data irrespective of system failures.

OS File System Storage Based Approach

  • Files of records – used for data storage
    • Data redundancy – wastage of space.
    • Maintaining consistency becomes difficult.
  • Record structures – hard coded into the programs
    • Structure modifications – hard to perform.
  • Each different data access request (a query)
    • Performed by a separate program.
    • Difficult to anticipate all such requests.
  • Creating the system
    • Requires a lot of effort.
  • Managing concurrent access and failure recovery are difficult.

DBMS Approach


  • Separation of data and metadata
  • Flexibility of changing metadata
  • Program-data independence

Data access language

  • Standardized – SQL
  • Ad-hoc query formulation – easy

System development

  • Less effort required
  • Concentration on logical level design is enough
  • Components to organize data storage process queries, manage concurrent access, recovery from failures, manage access control are all available

Data Model

Collection of conceptual tools to describe the database at a
certain level of abstraction.

  • Conceptual Data Model
    • A high level description
    • Useful for requirements understanding.
  • Representational Data Model
    • Describing the logical representation of data without giving details of physical representation.
  • Physical Data Model
    • Description giving details about record formats, file structures etc.

E/R (Entity/Relationship) Model

  • A conceptual level data model.
  • Provides the concepts of entities, relationships and attributes.

The University Database Context

Entities: student, faculty member, course, departments etc.

Relationships: enrollment relationship between student & course, employment relationship between faculty member, department etc.

Attributes: name, rollNumber, address etc., of student entity, name, empNumber, phoneNumber etc., of faculty entity etc.

More details will be given in the E/R Model Module.

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Also Read – Introduction to Android Development

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