1. Introduction to Database Management Systems

2. Motivation
Organisations are increasingly aware of the importance of information in the solution of their problems.
Because of decreasing cost of data storage, organisations store increasing quantities of data.
This data must be managed in the most efficient and effective manner.

3. The Database Approach
Organizations must have access to operational data that is
accurate
timely
convenient
up-to-date
secure but available
As control decentralizes in an organization, there is a danger that data management decentralizes as well.

4. Dangers of Decentralized Data Management
Redundancy
Inconsistency
Incompatibility
Different formats
Different constraints
Different models of the data
Inaccuracy
Insecurity
Non-accountability
Inflexibility

5. Integration and Sharing
Data should be
integrated
the database can be regarded as a unification of several otherwise distinct data files
shared
individual pieces of data in the database can be shared among several different users

6. Data Management Objective Requirements
Model a part of the world of the real world accurately and efficiently to give user useful data
Requirements
Flexibility
Accuracy
Reliability
Accessibility
Efficiency

7. Data Modelling: Abstraction Again
In modelling the data, we again use abstraction. We hide (irrelevant) detail and concentrate on the general and common attributes of a set of objects
Example:
Real world:
Student
Model:
ST(id, name, dob, grade history)

8. Definition of a Database
A database (DB) is a collection of interrelated computer files, whose data contents and structure are described in a data dictionary and which is under the control of a database management system (DBMS)

9. Database Management Systems
A database management system is a collection of programs that carry out activities on a database, including
setting up storage structures
loading data
accepting and performing updates
accepting data requests from users and programs.

10. Functions of a DBMS A good DBMS performs the following functions
maintain data dictionary
support multiple views of data
enforce integrity constraints
enforce access constraints
support concurrency control
support backup and recovery procedures
support logical transactions

11. Advantages of Using a DBMS
All applications access a common DB. So, details related to data storage and access are removed from programs and users.
Hence
less redundancy
less risk of inconsistency
maintenance of data integrity
application of access restrictions
balance between different requirements
data independence

12. Layered Structure of a Database
We can regard a database as having a layered structure
External Schema
Conceptual Schema
Internal Schema

13. Schemas and Instances
A schema is the overall design of the database. It describes the data contents, structure and some other aspects of the database also called the intension of the database
The instance is the collection of data stored in the database at a particular time, also called the extension of the database.

14. Data Independence: External schema
Different users often need different views of the data.
Example:
Bursar needs to have access to financial information on a student
Head of Department needs access to academic information.
An external schema is a description of part of the DB as seen by an application programmer or a user

15. Conceptual Schema
Representation of the logical structure of the information content of the DB.
Abstracts away from the actual physical storage.
The data “as it really is”.
It is, in a sense, a composite of all the external schemata.

16. Internal Schema
The internal schema describes the data as it is physically stored.
For example,
record structure
types of fields in a record
existence of primary and secondary indexes

17. Data Independence
Higher levels should be immune to changes at the lower level.
Physical data independence:
changes at the internal schema (e.g., changes in record structure or indexes) do not affect the conceptual schema
Logical data independence
changes at the conceptual schema (e.g., addition of further fields in a record) do not affect the external schema.

18. Importance of Data Independence
Similarity between data independence and the use of abstract data types.
Immunity to lower-level implementation details.
Possibility of adding new applications without having to restructure the data base.