Ch-1-Introduction-to-Database.pdf

CHAPTER 1: INTRODUCTION TO
DATABASE MANAGEMENT SYSTEM
Prepared By: Dr. Vipul Vekariya
.

CHAPTER 1: INTRODUCTION
 Purpose of Database Systems
 Database Languages
 Relational Databases
 Database Design
 Data Models
 Database Internals
 Database Users and Administrators
 Overall Structure
 History of Database Systems

DATA VS INFORMATION
 Data are row or isolated facts from which the required information is
produced.
 Data are distinct piece of information ,usually formatted in special way.
 They are binary computer representation of stored logical entities.
 Data can exit in variety of the form.
 Number or text on a paper , bit or byte stored in computer, fact stored in
persons mind.
 Data also can be an object such as document, photographic image and
video data.

DATA VS INFORMATION(CONT.)
 Data and information are closely related.
 Information is processed, organized, or summarize data.
 Data are processed to create information which is meaningful to the
user.
 Information is used for make decision or to interpret the data to get
the meaning.
 Database may contain either data or information( or both), according
to organization needs.

DATA WAREHOUSE
 Data warehouse is a collection of data designed to support
management in the decision making process.
 It is subject oriented, integrated, time variant collection of data.
 It is a unique kind of database which focus on business
intelligence and decision making process.
 It contains wide Varity of data that represent coherent picture of
business condition at a single point of time.

WHY DATABASE?
 Compactness : no paper works ( no Bunch of file)
 Speed: machine can retrieve data faster then human.
 Less drudgery: maintain files by hand is eliminating.
 Currency: accurate and up to date information is available on
demand.
 Protection : data can be better protected against unintentional
loss and unlawful access.

DATABASE MANAGEMENT SYSTEM (DBMS)
 A DBMS is collection of logically related data stored together that
is defined to meet the information needs of an organization.
 A DBMS is a collection of persistent data that is used by
application system of some given enterprise.
 It is also say that, is a collection of interrelated data stored
together without harmful or unnecessary redundancy.
 Finally it is just computerized record keeping system.
 A DBMS is a collection of interrelated data and a set of program
to access those data.

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
 Difficulty in accessing data
 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
 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

PURPOSE OF DATABASE SYSTEMS (CONT.)
 Drawbacks of using file systems (cont.)
 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
 Poor data control
 Limited data sharing
 Database systems offer solutions to all the above problems

DATABASE SYSTEM ENVIRONMENT
 Data
 Hardware
 Software
 User(people)
USER
Application
Program
Physical
Databse
Data Entry and
Reports

BENEFIT OF DBMS
 The data can be shared
 Redundancy can be reduced
 Inconsistency can be avoided
 Transaction support can be provided
 Integrity can be maintained
 Security can be enforced
 Conflicting requirement can be balanced
 Standards can be enforced.
 Increased concurrency
 Improved backup and recovery services
 Improved data quality

INSTANCES AND SCHEMAS
 Similar to types and variables in programming languages
 Schema – the overall design of the database is called database schema.
 Example: The database consists of information about a set of
customers and accounts and the relationship between them)
 The plan of the database is known as schema.
 Analogous to type information of a variable in a program
 Instance – the collection of information stored in the database at a
particular point in time.
 Analogous to the value of a variable

DATA MANIPULATION LANGUAGE (DML)
 A DML is a language that enable user to access or manipulate
the data.
 DML also known as query language
 Retrieval of information
 Insertion of new information
 Deletion of information
 Modification of information
 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),
branch_name char(10),
balance integer)
 Database schema
 Data storage and definition language
 Specifies the storage structure and access methods used
 Integrity constraints
 Domain constraints
 Referential integrity (e.g. branch_name must correspond to a
valid branch in the branch table)
 Authorization

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

DATA MODELS
 A collection of tools for describing
 Data
 Data relationships
 Data semantics
 Data constraints
 It is a way to describe the design of the database.
 Types of data model:
 Relational model
 Entity-Relationship data model (mainly for database design)
 Object-based data models (Object-oriented and Object-relational)
 Network model
 Hierarchical model

RELATIONAL MODEL
 Dr. E.F. Codd of IBM research first introduced Relational data
model.
 The relational model use a collection of table to represent both
data and relationship among those data.
 Each table has multiple column.
 Each column has unique name.
 The relational data model is the most widely used the data model.
Attributes

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:

HIERARCHICAL MODEL
 This model is represented by an up- down tree.
 The user perceives the hierarchical database as a hierarchy of
segments.
 A segments is equivalent of file system records type.
University
Department
Faculty
Course

NETWORK DATA MODEL.
 It is similar to hierarchical model except that a record can have
multiple parents.
A
B
D E
C
F

Ch-1-Introduction-to-Database.pdf

THE THREE LEVEL ANSI-SPARC DATABASE
ARCHITECTURE
 Internal Level:
 Is the one closest to the physical storage.
 It is the one concerned with the way how the data is stored
inside the system.
 It describe the data structure, file structure, and access method
to be used by the database.
 External Level:
 Is the one closest to the user.
 It is the one concerned with the way the data is seen by
individual users.
 In this level user seen only interested data for them.
 Conceptual Level:
 is a level of indirection between other two.
 All the database entities and the relationship among them are
included.

LEVELS OF ABSTRACTION
 Physical level: describes how a record (e.g., customer) is stored.
 storage space allocation for data storage.
 record description for storage with storage size.
 record placement
 Data compression and data encryption technique.
 Logical level: describes data stored in database, and the relationships
among the data.
type customer = record
customer_id : string(20);
customer_name : string(45);
customer_street : string(20);
customer_city : string(20);
end;
Constraint on data.
Check to retain data consistency and integrity
security information
 View level: application programs hide details of data types. Views can
also hide information (such as an employee’s salary) for security
purposes.

DATA ABSTRACTION
Logical
Level
Physical
Level
View Level
View 1 View 2 View n
…
How data is actually stored ?
e.g. are we using disks ? Which
file system ?
What data is stored ?
describe data properties such as
data semantics, data relationships
What data users and
application programs
see ?

DATABASE MANAGEMENT SYSTEM
INTERNALS
 Storage management
 Query processing
 Transaction processing

STORAGE MANAGEMENT
 Storage manager is a program module that provides the
interface between the low-level data stored in the database and
the application programs and queries submitted to the system.
 The storage manager is responsible to the following tasks:
 Interaction with the file manager
 Efficient storing, retrieving and updating of data
 Authorization and integrity manager: check for integrity
constraint and check for authority of user.
 Transaction manager: responsible for database remains in
consistent state when system failure. And concurrent
transaction execution.
 File manager: manages the allocation of space on disk storage.
 Buffer manager: is responsible for fetching data from disk
storage in to main memory and deciding what data to cache in
memory.
 Data dictionary: which store metadata ( data about data)
 Indices: which can provide fast access.

QUERY PROCESSING
1.Parsing and translation
2.Optimization
3.Evaluation

QUERY PROCESSING (CONT.)
 DDL Interpreter: which interpreter DDL statements and
record the definition in the data dictionary.
 DML Complier: Which translate DML statements in to
low level instruction.
 Query Evolution Engine: which execute low level
instruction generated by DML complier.

TRANSACTION MANAGEMENT
 A transaction is a collection of operations that performs a single
logical function in a database application
 Transaction-management component ensures that the
database remains in a consistent (correct) state despite system
failures (e.g., power failures and operating system crashes) and
transaction failures.
 Concurrency-control manager controls the interaction among
the concurrent transactions, to ensure the consistency of the
database.

DATABASE USERS
Users are differentiated by the way they expect to interact with
the system
 Application programmers – is computer professional who write
application program and access database.
 Sophisticated users –(without writing program) form requests
in a database query language
 Specialized users – write specialized database applications that
do not fit into the traditional data processing framework
 Naïve users – invoke one of the permanent application programs
that have been written previously
 Examples, people accessing database over the web, bank
tellers, clerical staff

DATABASE ADMINISTRATOR
 Coordinates all the activities of the database
system
 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
 Granting users authority to access the database
 Periodically Backing up data
 Ensuring that enough free disk space is available or
not.
 Monitoring performance and responding to changes
 Database tuning

DATA DICTIONARY
 Data dictionary (or data repository) or system catalog is an important
part of the DBMS.
 It contains data about data (or metadata).
 It means that it contains the actual database descriptions used by the
DBMS.
 In most DBMSs, the data dictionary is active and integrated. It means
that the DBMS checks the data dictionary every time the database is
accessed.
 The data dictionary contains the following information.
 Description of schema of database.
 Schemas, mappings and constraints
 Description of the database user, their responsibilities and rights.
 Descriptions of statistics such as frequencies of queries and
transactions and access counts to different portion of database. .
 Description about physical database design, such as storage structures,
access paths ,file and record size etc.
 Descriptions about users of DBMS and their access rights.

DBMS VS RDBMS
 DBMS : Data Base Management System is a process of managing data for efficient
retrieval & storage of data.
 Ex: Sybase , FoxPro
 RDBMS : The database which is used by relations(tables) to acquire information
retrieval are known as RDBMS
 EX: SQL, ORACLE,MY-SQLSERVER
DBMS does not impose any constraints or security with regard to data
manipulation. It is user or the programmer responsibility to ensure the ACID
PROPERTY of the database
In DBMS Normalization process will not be present.
It supports Single User only
It treats Data as Files internally
It supports 3 rules of E.F.CODD out off 12 rules
It requires low Software and Hardware Requirements.

RDBMS
 RDBMS is based on relational model, in which data is represented in the
form of relations, with enforced relationships between the tables.
 RDBMS defines the integrity constraint for the purpose of holding ACID
PROPERTY.
 In RDBMS, normalization process will be present to check the database
table consistency.
 RDBMS helps in recovery of the database in case of loss of database due to
system failure or any other reason.
 It supports multiple users.
 It treats data as Tables internally.
 It supports minimum 6 rules of E.F.CODD.
 It requires High software and hardware requirements.

DBMS VS RDBMS
DBMS RDMS
Data handle as a File oriented
system
Data handle as a in form of table
DBMS does not support the
client server Architecture
Most of the RDBMS support the
client server architecture
DBMS does not support
distributed databases
RDBMS support distributed
database
There is no security of data There are multiple level of
security
DBMS may satisfy less then 7
rule of Dr. E. F. Codd
RDBMS satisfy more than 7 rule
of Dr. E. F. Codd
Naming Conventions
Field Columns, Attributes
Record Row, Tuple,Entity
File Table, relation, Entity class

DATA INDEPENDENCY
 It is a major objective of DBMS in organization.
 It is a characteristics of DBMS to change the schema at one
level without having to change the schema at the next higher
level.
 Physical data independency
 Logical data independency

PHYSICAL DATA INDEPENDENCY
 Immunity of the conceptual level to change in the internal
schema is referred to a Physical data independency.
 Means change in the physical storage of the data.
 Change different file structure, storage structure, different
storage devices, modify index or hashing algorithm.
 LOGICAL DATA INDEPENDENCY
 Immunity of the external level to change in the conceptual
schema is referred to a logical data independency
 Change in logical structure of data.
 Addition and deletion of entities , change in relationship of
table

MAPPING
 The process of transforming request and result
between three levels are called mapping.

SOFTWARE ARCHITECTURE
Prepared By: Vipul Vekariya
M.E(Computer)

FILE SHARING ARCHITECTURE :
 where the server downloads files from the shared location
to the desktop environment.
 The requested user job is then run both logic and data in
the desktop environment.
 The main problem with this setup is that file sharing gets
strained when the number of online users grow
significantly.
 Also network traffic got congested.
 Works if
 Shared usage is low
 Data transferred is low

CLIENT/SERVER ARCHITECTURE( TWO TIER)
 Database server to replace File server
 Query based approach
 Reduced traffic, since required content is only transferred
 remote procedure calls or standard query language statements are
being used by clients to communicate with servers.
 The application exists entirely on the client PC while the database
sits out on a server machine.
 the full processing load is lying onto the PC while the more powerful
server machine act as a traffic controller between the application and
the database.
 arises a very high Hang-up on scalability, availability and
performance on the system.
 Another main problem with any two-tiered client/server approach is
that of maintenance.

TWO TIER ARCHITECTURE
 It mainly comprises of two layers:
Pictorial Representation Of 2-TIER

THREE TIER ARCHITECTURE
 In order to address the above-mentioned issues in an effective way,
software developers community came with an evolutionary but
effective and efficient solution referred to as "three-tier
architecture".
 The first tier is called as the presentation layer and it normally
consists of a graphical user interface.
 The middle tier consists of the application logic and the third tier is
the data layer.
 The middle tier composes business application logic code, which the
user calls upon through the front-end graphical user interface to
retrieve the desired data.
 The middle tier can perform queuing, application execution, locating.
 The third tier contains the data that is needed for the application..
The data can be from any source of information such an enterprise
database like Oracle, MS SQL Server, a set of XML documents.

NEW THREE TIER ARCHITECTURE:
 It mainly comprises of three layers
Pictorial Representation of New Environment

ADVANTAGE
 Improved Scalability, availability, and performance
 Improved flexibility, and extensibility of business systems
 Three-tier systems are more flexible and extensible than their two-tier
systems as the business logic and services such as security, persistence,
transactions etc reside on the middle-tier and transparent to the client
applications.
 This tends to make these services being applied automatically to client
requests and any changes made in the business logic code do not reflect
on the clients in any way.
 Clustering makes three-tier systems more available and scalable
because multiple servers and resources can support fail-over and
balance the word loads of a growing client population.

Ch-1-Introduction-to-Database.pdf

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