The document provides an overview of database management systems (DBMS), explaining their purpose, architecture, and the various types of users and database languages involved. It outlines the challenges overcome by DBMS, such as data redundancy, integrity problems, and concurrent access. Additionally, it details the levels of abstraction in databases, including physical, logical, and view levels, along with different data models and the roles of database administrators.

1. Introduction to DBMS
 Purpose of Database System
 Views of data
 Data Models
 Database Languages
 Database System Architecture
 Database users and Administrator

2. Database Management System (DBMS)
 Collection of interrelated data
 Set of programs to access the data
 DMBS contains information about a particular
enterprise
 DBMS provides an environment that it both
convenient and efficient to use

3. Purpose of Database Systems
 Data redundancy and inconsistency
 Difficulty in accessing data
 Data isolation – multiple files and formats
 Integrity problems
 Atomicity of updates
 Concurrent access by multiple users
 Security problems
Database management systems were developed to
handle the following difficulties of typical file-
processing systems supported by conventional
operating systems:

4.  Banking: all transactions
 Airlines: reservations, schedules
 Universities: registration, grades
 Sales: customers, products, purchases
 Online retailers: order tracking, customized
recommendations
 Manufacturing: production, inventory, orders, supply chain
 Human resources: employee records, salaries, tax
deductions
DATABASE APPLICATIONS

5. Levels of Abstraction
 Physical level: describes how a record (e.g., customer) is stored.
 Logical level: describes data stored in database, and the relationships
among the data.
type customer = record
customer_id : string;
customer_name : string;
customer_street : string;
customer_city : string;
end;
 View level: application programs hide details of data types. Views can also
hide information (such as an employee’s salary) for security purposes.

6. Views of Data
An architecture for a database system
View 1
Physical
level
Logical
level
View 2 View n
…
View level

7. Instances and Schemas
 Similar to types and variables in programming languages
 Schema – the logical structure of the database
 Example: The database consists of information about a set of customers
and accounts and the relationship between them)
 Analogous to type information of a variable in a program
 Physical schema: database design at the physical level
 Logical schema: database design at the logical level
 Instance – the actual content of the database at a particular point in time
 Analogous to the value of a variable
 Physical Data Independence – the ability to modify the physical schema
without changing the logical schema
 Applications depend on the logical schema
 In general, the interfaces between the various levels and components
should be well defined so that changes in some parts do not seriously
influence others.

8. Data Models
 A collection of tools for describing
 Data
 Data relationships
 Data semantics
 Data constraints
 Relational model
 Entity-Relationship data model (mainly for database design)
 Object-based data models (Object-oriented and Object-relational)
 Semi structured data model (XML)
 Other older models:
 Network model
 Hierarchical model

9. Database Languages
• Specification notation for defining the database schema
• DDL compiler generates a set of tables stored in a data
dictionary
• Data dictionary contains metadata (data about data)
• Data storage and definition language – special type of
DDL in which the storage structure and access methods
used by the database system are specified
Data Definition Language

10. Data Definition Language-DDL
• Data Definition Language (DDL) statements are used to
define the database structure or schema.
Some examples:
• CREATE - to create objects in the database
• ALTER - alters the structure of the database
• DROP - delete objects from the database
TRUNCATE - remove all records from a table, including
all spaces allocated for the records are removed
• COMMENT - add comments to the data dictionary
• RENAME - rename an object

11. Data Manipulation Language ( DML )
 Language for accessing and manipulating the data
organized by the appropriate data model
 Two classes of languages
 Procedural – user specifies what data is required and how to
get those data
 Nonprocedural – user specifies what data is required
without specifying how to get those data

12. Data Manipulation Language (DML)
• Data Manipulation Language (DML) statements are used for
managing data within schema objects.
Some examples:
SELECT - Retrieve data from the a database
• INSERT - Insert data into a table
• UPDATE - Updates existing data within a table
• DELETE - deletes all records from a table, the space for the records
remain
• MERGE - UPSERT operation (insert or update)
• CALL - Call a PL/SQL or Java subprogram
• EXPLAIN PLAN - explain access path to data
• LOCK TABLE - control concurrency

13. Data Control Language (DCL)
 Data Control Language (DCL) statements.
Some examples:
GRANT - gives user's access privileges to database
 REVOKE - withdraw access privileges given with the
GRANT command

14. Database System Architecture

15. Database Administrator(DBA)
 Coordinates all the activities of the database system; the
database administrator has a good understanding of the
enterprise’s information resources and needs:
 Database administrator’s duties include:
 Schema definition
 Storage structure and access method definition
 Schema and physical organization modification
 Granting user authority to access the database
 Specifying integrity constraints
 Monitoring performance and responding to changes in requirements

16. Database Users
• Users are differentiated by the way they expect to interact
with the system.
• Application programmers: interact with system through
DML calls.
• Specialized users: write specialized database applications
that do not fit into the traditional data processing
framework
• Sophisticated users: form requests in a database query
language.
• Naive users: invoke one of the permanent application
programs that have been written previously

17. BY:
Ms.K.Gayathri,
Assistant Professor,
Dept of Computer Science,
Bon Secours College for Women,
Thanjavur.