INTRODUCTION OF DATA BASE

Chapter 1: Introduction
Purpose of Database Systems
View of Data
Database Languages
Relational Databases
Database Design

Database Management System
(DBMS)
DBMS contains information about a particular enterprise
Collection of interrelated data
Set of programs to access the data
An environment that is both convenient and efficient to use
•Database Applications:
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
•Databases touch all aspects of our lives

Purpose of Database Systems
• In the early days, database applications were built
directly on top of file systems
• Drawbacks of using file systems to store data:
– Data redundancy and inconsistency
• Multiple file formats, duplication of information in different files
– Difficulty in accessing data
• Need to write a new program to carry out each new task
– Data isolation — multiple files and formats
– Integrity problems
• Integrity constraints (e.g. account balance > 0) become “buried” in
program code rather than being stated explicitly
• Hard to add new constraints or change existing ones

Purpose of Database Systems (Cont.)
• Drawbacks of using file systems (cont.)
– Atomicity of updates
• Failures may leave database in an inconsistent state with partial
updates carried out
• Example: Transfer of funds from one account to another should
either complete or not happen at all
– Concurrent access by multiple users
• Concurrent accessed needed for performance
• Uncontrolled concurrent accesses can lead to inconsistencies
– Example: Two people reading a balance and updating it at the same time
– Security problems
• Hard to provide user access to some, but not all, data
• Database systems offer solutions to all the above
problems

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 : integer;
end;
• View level: application programs hide details of data
types. Views can also hide information (such as an
employee’s salary) for security purposes.

View of Data
An architecture for a database system

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.

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)
• Semistructured data model (XML)
• Other older models:
– Network model
– Hierarchical model

Data Manipulation Language (DML)
• Language for accessing and manipulating the data
organized by the appropriate data model
– DML also known as query language
• Two classes of languages
– Procedural – user specifies what data is required and
how to get those data
– Declarative (nonprocedural) – user specifies what
data is required without specifying how to get those
data
• SQL is the most widely used query language

Data Definition Language (DDL)
• Specification notation for defining the database schema
Example: create table account (
account-number char(10),
balance integer)
• DDL compiler generates a set of tables stored in a data
dictionary
• Data dictionary contains metadata (i.e., data about data)
– Database schema
– Data storage and definition language
• Specifies the storage structure and access methods used
– Integrity constraints
• Domain constraints
• Referential integrity (references constraint in SQL)
• Assertions
– Authorization

Relational Model
Example of tabular data in the relational model
Attributes

SQL
• SQL: widely used non-procedural language
– Example: Find the name of the customer with customer-id 192-83-
7465
select customer.customer_name
from customer
where customer.customer_id = ‘192-83-7465’
– Example: Find the balances of all accounts held by the customer with
customer-id 192-83-7465
select account.balance
from depositor, account
where depositor.customer_id = ‘192-83-7465’ and
depositor.account_number = account.account_number
• Application programs generally access databases through one of
– Language extensions to allow embedded SQL
– Application program interface (e.g., ODBC/JDBC) which allow SQL
queries to be sent to a database

Database Design
The process of designing the general structure of the database:
• Logical Design – Deciding on the database schema. Database
design requires that we find a “good” collection of relation
schemas.
– Business decision – What attributes should we record in the database?
– Computer Science decision – What relation schemas should we have
and how should the attributes be distributed among the various
relation schemas?
• Physical Design – Deciding on the physical layout of the database

The Entity-Relationship Model
• Models an enterprise as a collection of entities and relationships
– Entity: a “thing” or “object” in the enterprise that is distinguishable
from other objects
• Described by a set of attributes
– Relationship: an association among several entities
• Represented diagrammatically by an entity-relationship diagram:

INTRODUCTION OF DATA BASE

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INTRODUCTION OF DATA BASE