term paper on dbms

8/18/2019 Term paper on DBMS

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TERM PAPER ONROLE OF DBMS IN

EDUCATIONAL INSTITUTIONS

Submitted To

Dr. Md. Akram HossainAssociate Professor

Submitted By

Abdullah-Al-Kashem (ID: 20-006)Md. Imran Shahed (ID: 20-011)Lubna Rahman Lina (ID: 20-017)Md. Imtiaz Hossain (ID: 20-031)

Munshi Jahidul Islam (ID: 20-032)Md. Ariful Alam (ID: 20-040)Md. Emadul Haq (ID: 20-045)Md. Rezwan-Ul-Haque (ID: 20-055) Nasir Uddin (ID: 20-070)Md. Al-Mamun Riyadh (ID: 20-079)

Department of Management Information Systems

University of Dhaka

Date of Submission: 21 December, 2015


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Table of Content

ontents

Executive Summary .......................................................................................................................... 4

Introduction....................................................................................................................................... 5

What is DBMS .................................................................................................................................. 6

Ancient History ............................................................................................................................. 6

1968 File-Based............................................................................................................................. 6

Hierarchical data model ................................................................................................................. 6

Network data model....................................................................................................................... 7

1970-present Era of relational database and Database Management System ................................... 7

DBMS Characteristics ....................................................................................................................... 8

Real-world entity........................................................................................................................... 8

Relation-based tables..................................................................................................................... 8

Isolation of data and application..................................................................................................... 8

Less redundancy ............................................................................................................................ 8

Consistency................................................................................................................................... 8

Query Language ............................................................................................................................ 8

ACID Properties ............................................................................................................................ 8

Multiuser and Concurrent Access .................................................................................................. 9

Multiple views ............................................................................................................................... 9

Security ......................................................................................................................................... 9

Users ................................................................................................................................................. 9

Entity-Relationship Model............................................................................................................... 11

Entity .......................................................................................................................................... 11

Relationship ................................................................................................................................ 11

Mapping cardinalities .................................................................................................................. 11

Database Schema............................................................................................................................. 12

Classifications of database............................................................................................................... 13

Design and modeling of DBMS in Educational Institutions .............................................................. 16

Banking....................................................................................................................................... 16

Airlines ....................................................................................................................................... 16

Universities ................................................................................................................................. 16

Sales ............................................................................................................................................ 16


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Online retailers ............................................................................................................................ 16

Manufacturing............................................................................................................................. 16

Human resources ......................................................................................................................... 16

Modification of the Database – Deletion ...................................................................................... 21

Modification of the Database – Insertion ....................................................................................... 21

Modification of the Database – Updates ....................................................................................... 22


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List of Figures

Figure 1: DBMS Users ...................................................................................................................... 9

Figure 2: DBMS Architecture.......................................................................................................... 10

Figure 3: Entity Relation Model....................................................................................................... 11

Figure 4: View of Data .................................................................................................................... 13

Figure 5: The ―Student‖ Table ......................................................................................................... 17

Figure 6: The ―Course‖ Table .......................................................................................................... 18

Figure 7: Showing all data from "course" Table ............................................................................... 19


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Executive Summary

Database Management Systems (DBMSs) are a ubiquitous and critical component of modern

computing, and the result of decades of research and development in both academia and

industry. Historically, DBMSs were among the earliest multi-user server systems to be

developed, and thus pioneered many systems design techniques for scalability and relia-bility

now in use in many other contexts. While many of the algorithms and abstractions used by a

DBMS are textbook material, there has been relatively sparse coverage in the literature of the

systems design issues that make a DBMS work. This paper presents an architectural

discussion of DBMS design principles, including process models, parallel architecture,

storage system design, transaction system implementation, query processor and optimizer

architectures, and typical shared components and utilities. Successful commercial and open-

source systems are used as points of reference, particularly when multiple alternative designs

have been adopted by different groups.


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Introduction

Data are raw facts that constitute building blocks of information. Database is a collection of

information and a means to manipulate data in a useful way, which must provide proper

storage for large amounts of data, easy and fast access and facilitate the processing of

data. Or we can say that Database is a collection of related data and data is a collection of

facts and figures that can be processed to produce information.

Mostly data represents recordable facts. Data aids in producing information, which is based

on facts. For example, if we have data about marks obtained by all students, we can then

conclude about toppers and average marks.

Database Management System (DBMS) is a set of software that is used to define, store,

manipulate and control the data in a database. A database management system stores data in

such a way that it becomes easier to retrieve, manipulate, and produce information.

From pre-stage flat-file system, to relational and object-relational systems, database

technology has gone through several generations and its 40 years history.


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What is DBMS

A database management system (DBMS) is a computer software application that interacts

with the user, other applications, and the database itself to capture and analyze data. A

general-purpose DBMS is designed to allow the definition, creation, querying, update, and

administration of databases. Well-known DBMSs include MySQL, PostgreSQL, Microsoft

SQL Server, Oracle, Sybase and IBM DB2. A database is not generally portable across

different DBMSs, but different DBMS can interoperate by using standards such as SQL and

ODBC or JDBC to allow a single application to work with more than one DBMS.

Evolution of the Database

Ancient History

Data are not stored on disk; programmer defines both logical data structure and physical

structure, such as storage structure, access methods, I/O modes etc. One data set per program:

high data redundancy. There is no persistence; Random access memory (RAM) is expensive

and limited, programmer productivity low.

1968 File-Based

Predecessor of database, Data maintained in a flat file. Processing characteristics determined

by common use of magnetic tape medium. Data are stored in files with interface between

programs and files. Mapping happens between logical files and physical file, one file

corresponds to one or several programs, various access methods exits, e.g., sequential,indexed, random requires extensive programming in third-generation language such as

COBOL, BASIC.

Separation and isolation: Each program maintains its own set of data, users of one program

may not aware of holding or blocking by other programs. Duplication: Same data is held by

different programs, thus, wastes space and resources. High maintenance costs such as ensuing

data consistency and controlling access sharing granularity is very coarse Weak security

1968-1980 Era of non-relational database: A database provides integrated and structured

collection of stored operational data which can be used or shared by application

systems. Prominent hierarchical database model was IBM’s first DBMS called IMS.Prominent network database model was CODASYL DBTG model; IDMS was the most

popular network DBMS.

Hierarchical data model

Mid 1960s Rockwell partner with IBM to create information Management System (IMS),

IMS DB/DC lead the mainframe database market in 70 ’s and early 80’s. Based on binary

trees. Logically represented by an upside down tree, one-to many relationship between parent

and child records. Efficient searching; Less redundant data; Data independence; Database

security and integrity.

https://en.wikipedia.org/wiki/Computer_softwarehttps://en.wikipedia.org/wiki/Software_portabilityhttps://en.wikipedia.org/wiki/Technical_standardhttps://en.wikipedia.org/wiki/SQLhttps://en.wikipedia.org/wiki/ODBChttps://en.wikipedia.org/wiki/JDBChttps://en.wikipedia.org/wiki/JDBChttps://en.wikipedia.org/wiki/ODBChttps://en.wikipedia.org/wiki/SQLhttps://en.wikipedia.org/wiki/Technical_standardhttps://en.wikipedia.org/wiki/Software_portabilityhttps://en.wikipedia.org/wiki/Computer_software


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Complex implementation: Difficult to manage and lack of standards, such as problem to add

empty nodes and can’t easily handle many-many relationships. Lacks structural

independence, such add up application programming and use complexity.

Network data model

Early 1960s, Charles Bachmann developed first DBMS at Honeywell, Integrated Data Store (

IDS). It standardized in 1971 by the CODASYL group (Conference on Data Systems

Languages). Directed acyclic graph with nodes and edges: Identified 3 database component:

Network schema database organization; Subschema view s of database per user; Data

management language -- at low level and procedural. Each record can have multiple parents:

Composed of sets relationships, a set represents a one--many relationship between the owner

and the member. Each set has owner record and member record member may have several

owners. Main problem: System complexity and difficult to design and maintain; Lack of

structural independence. The distinction of storing data in files and databases is that databases

are intended to be used by multiple programs and types of users.

1970-present Era of relational database and Database Management System

Based on relational calculus, shared collection of logically related data and a description of

this data, designed to meet the information needs of an organization; System

catalog/metadata provides description of data to enable program-data independence; logically

related data comprises entities, attributes, and relationships of an organization ’s information.

Data abstraction allows view level, a way of presenting data to a group of users and logical

level, how data is understood to be when writing queries. 1970: Ted Codd at IBM’s San Jose

Lab proposed relational models. Two major projects start and both were operational in late1970s INGRES at University of California, Berkeley became commercial and followed up

POSTGRES which was incorporated into Informix. System R at IBM san Jose Lab, later

evolved into DB2, which became one of the first DBMS product based on the relational

model. (Oracle produced a similar product just prior to DB2.)

1976: Peter Chen defined the Entity-relationship(ER) model

1980s: Maturation of the relational database technology, more relational based DBMS were

developed and SQL standard adopted by ISO and ANSI.

1985: Object-oriented DBMS (OODBMS) develops. Little success commercially becauseadvantages did not justify the cost of converting billions of bytes of data to new format.

1990s: incorporation of object-orientation in relational DBMSs, new application areas, such

as data warehousing and OLAP, web and Internet, Interest in text and multimedia, enterprise

resource planning (ERP) and management resource planning (MRP)

1991: Microsoft ships access, a personal DBMS created as element of Windows gradually

supplanted all other personal DBMS products.

1995: First Internet database applications


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1997: XML applied to database processing, which solves long-standing database

problems. Major vendors begin to integrate XML into DBMS products.

DBMS Characteristics

Traditionally, data was organized in file formats. DBMS was a new concept then, and all the

research was done to make it overcome the deficiencies in traditional style of data

management. A modern DBMS has the following characteristics:

Real-world entity

A modern DBMS is more realistic and uses real-world entities to design its architecture. It

uses the behavior and attributes too. For example, a school database may use students as an

entity and their age as an attribute.

Relation-based tables

DBMS allows entities and relations among them to form tables. A user can understand the

architecture of a database just by looking at the table names.

Isolation of data and application

A database system is entirely different than its data. A database is an active entity, whereas

data is said to be passive, on which the database works and organizes. DBMS also stores

metadata, which is data about data, to ease its own process.

Less redundancy DBMS follows the rules of normalization, which splits a relation when any of its attributes is

having redundancy in values. Normalization is a mathematically rich and scientific process

that reduces data redundancy.

Consistency

Consistency is a state where every relation in a database remains consistent. There exist

methods and techniques, which can detect attempt of leaving database in inconsistent state. A

DBMS can provide greater consistency as compared to earlier forms of data storing

applications like file-processing systems.

Query Language

DBMS is equipped with query language, which makes it more efficient to retrieve and

manipulate data. A user can apply as many and as different filtering options as required to

retrieve a set of data. Traditionally it was not possible where file-processing system was used.

ACID Properties

DBMS follows the concepts of Atomicity, Consistency, Isolation, and Durability (normally

shortened as ACID). These concepts are applied on transactions, which manipulate data in a


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database. ACID properties help the database stay healthy in multi-transactional environments

and in case of failure.

Multiuser and Concurrent Access

DBMS supports multi-user environment and allows them to access and manipulate data in parallel. Though there are restrictions on transactions when users attempt to handle the same

data item, but users are always unaware of them.

Multiple views

DBMS offers multiple views for different users. A user who is in the Sales department will

have a different view of database than a person working in the Production department. This

feature enables the users to have a concentrate view of the database according to their

requirements.

Security

Features like multiple views offer security to some extent where users are unable to access

data of other users and departments. DBMS offers methods to impose constraints while

entering data into the database and retrieving the same at a later stage. DBMS offers many

different levels of security features, which enables multiple users to have different views with

different features. For example, a user in the Sales department cannot see the data that

belongs to the Purchase department. Additionally, it can also be managed how much data of

the Sales department should be displayed to the user. Since a DBMS is not saved on the disk

as traditional file systems, it is very hard for miscreants to break the code.

Users

A typical DBMS has users with different rights and permissions who use it for different

purposes. Some users retrieve data and some back it up. The users of a DBMS can be broadly

categorized as follows −

Figure 1: DBMS Users

Administrators − Administrators maintain the DBMS and are responsible for administratingthe database. They are responsible to look after its usage and by whom it should be used.


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They create access profiles for users and apply limitations to maintain isolation and force

security. Administrators also look after DBMS resources like system license, required tools,

and other software and hardware related maintenance.

Designers − Designers are the group of people who actually work on the designing part of the

database. They keep a close watch on what data should be kept and in what format. Theyidentify and design the whole set of entities, relations, constraints, and views.

End Users − End users are those who actually reap the benefits of having a DBMS. End users

can range from simple viewers who pay attention to the logs or market rates to sophisticated

users such as business analysts.

The design of a DBMS depends on its architecture. It can be centralized or decentralized or

hierarchical. The architecture of a DBMS can be seen as either single tier or multi-tier. An n-

tier architecture divides the whole system into related but independent n modules, which can

be independently modified, altered, changed, or replaced. A 3-tier architecture separates itstiers from each other based on the complexity of the users and how they use the data present

in the database. It is the most widely used architecture to design a DBMS.

Figure 2: DBMS Architecture

Multiple-tier database architecture is highly modifiable, as almost all its components are

independent and can be changed independently.


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Entity-Relationship Model

Entity-Relationship (ER) Model is based on the notion of real-world entities and relationships

among them. While formulating real-world scenario into the database model, the ER Model

creates entity set, relationship set, general attributes and constraints. ER Model is best used

for the conceptual design of a database. ER Model is based on –

Entities and their attributes.

Relationships among entities.

These concepts are explained below:

Figure 3: Entity Relation Model

Entity

An entity in an ER Model is a real-world entity having properties called attributes. Everyattribute is defined by its set of values called domain. For example, in a school database, a

student is considered as an entity. Student has various attributes like name, age, class, etc.

Relationship

The logical association among entities is called relationship. Relationships are mapped with

entities in various ways. Mapping cardinalities define the number of association between two

entities.

Mapping cardinalities

one to one

one to many

many to one

many to many


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The main highlights of this model are −

Data is stored in tables called relations.

Relations can be normalized.

In normalized relations, values saved are atomic values.

Each row in a relation contains a unique value.

Each column in a relation contains values from a same domain.

Database Schema

A database schema is the skeleton structure that represents the logical view of the entire

database. It defines how the data is organized and how the relations among them are

associated. It formulates all the constraints that are to be applied on the data.

A database schema defines its entities and the relationship among them. It contains a

descriptive detail of the database, which can be depicted by means of schema diagrams. It’s

the database designers who design the schema to help programmers understand the database

and make it useful.


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Figure 4: View of Data

Classifications of database

One way to classify databases involves the type of their contents, for example: bibliographic,

document-text, statistical, or multimedia objects. Another way is by their application area, for

example: accounting, music compositions, movies, banking, manufacturing, or insurance. Athird way is by some technical aspect, such as the database structure or interface type. This

section lists a few of the adjectives used to characterize different kinds of databases.

An in-memory database is a database that primarily resides in main memory, but is typically

backed-up by non-volatile computer data storage. Main memory databases are faster than

disk databases, and so are often used where response time is critical, such as in

telecommunications network equipment.

An active database includes an event-driven architecture which can respond to conditions

both inside and outside the database. Possible uses include security monitoring, alerting,

https://en.wikipedia.org/wiki/Bibliographic_databasehttps://en.wikipedia.org/wiki/In-memory_databasehttps://en.wikipedia.org/wiki/Main_memoryhttps://en.wikipedia.org/wiki/Active_databasehttps://en.wikipedia.org/wiki/Active_databasehttps://en.wikipedia.org/wiki/Main_memoryhttps://en.wikipedia.org/wiki/In-memory_databasehttps://en.wikipedia.org/wiki/Bibliographic_database


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statistics gathering and authorization. Many databases provide active database features in the

form of database triggers.

A cloud database relies on cloud technology. Both the database and most of its DBMS reside

remotely, "in the cloud", while its applications are both developed by programmers and later

maintained and utilized by (application's) end-users through a web browser and Open APIs.

Data warehouses archive data from operational databases and often from external sources

such as market research firms. The warehouse becomes the central source of data for use by

managers and other end-users who may not have access to operational data. For example,

sales data might be aggregated to weekly totals and converted from internal product codes to

use UPCs so that they can be compared with ACNielsen data. Some basic and essential

components of data warehousing include extracting, analyzing, and mining data,

transforming, loading and managing data so as to make them available for further use.

A deductive database combines logic programming with a relational database, for example byusing the Datalog language. A distributed database is one in which both the data and the

DBMS span multiple computers. A document-oriented database is designed for storing,

retrieving, and managing document-oriented, or semi structured data, information.

Document-oriented databases are one of the main categories of NoSQL databases.

An embedded database system is a DBMS which is tightly integrated with application

software that requires access to stored data in such a way that the DBMS is hidden from the

application’s end-users and requires little or no ongoing maintenance.

End-user databases consist of data developed by individual end-users. Examples of these are

collections of documents, spreadsheets, presentations, multimedia, and other files. Several

products exist to support such databases. Some of them are much simpler than full-fledged

DBMSs, with more elementary DBMS functionality.

A federated database system comprises several distinct databases, each with its own DBMS.

It is handled as a single database by a federated database management system (FDBMS),

which transparently integrates multiple autonomous DBMSs, possibly of different types (in

which case it would also be a heterogeneous database system), and provides them with an

integrated conceptual view.

Sometimes the term multi-database is used as a synonym to federated database, though it mayrefer to a less integrated (e.g., without an FDBMS and a managed integrated schema) group

of databases that cooperate in a single application. In this case typically middleware is used

for distribution, which typically includes an atomic commit protocol (ACP), e.g., the two-

phase commit protocol, to allow distributed (global) transactions across the participating

databases.

A graph database is a kind of NoSQL database that uses graph structures with nodes, edges,

and properties to represent and store information. General graph databases that can store any

graph are distinct from specialized graph databases such as triplestores and network

databases.

https://en.wikipedia.org/wiki/Database_triggerhttps://en.wikipedia.org/wiki/Cloud_databasehttps://en.wikipedia.org/wiki/Cloud_computinghttps://en.wikipedia.org/wiki/Web_browserhttps://en.wikipedia.org/wiki/Open_APIhttps://en.wikipedia.org/wiki/Data_warehousehttps://en.wikipedia.org/wiki/Universal_Product_Codehttps://en.wikipedia.org/wiki/ACNielsenhttps://en.wikipedia.org/wiki/Data_mininghttps://en.wikipedia.org/wiki/Deductive_databasehttps://en.wikipedia.org/wiki/Logic_programminghttps://en.wikipedia.org/wiki/Dataloghttps://en.wikipedia.org/wiki/Distributed_databasehttps://en.wikipedia.org/wiki/Embedded_databasehttps://en.wikipedia.org/wiki/Federated_database_systemhttps://en.wikipedia.org/wiki/Heterogeneous_database_systemhttps://en.wikipedia.org/wiki/Middleware_%28distributed_applications%29https://en.wikipedia.org/wiki/Two-phase_commit_protocolhttps://en.wikipedia.org/wiki/Two-phase_commit_protocolhttps://en.wikipedia.org/wiki/Distributed_transactionhttps://en.wikipedia.org/wiki/Graph_databasehttps://en.wikipedia.org/wiki/Graph_%28data_structure%29https://en.wikipedia.org/wiki/Triplestorehttps://en.wikipedia.org/wiki/Network_database_modelhttps://en.wikipedia.org/wiki/Network_database_modelhttps://en.wikipedia.org/wiki/Network_database_modelhttps://en.wikipedia.org/wiki/Network_database_modelhttps://en.wikipedia.org/wiki/Triplestorehttps://en.wikipedia.org/wiki/Graph_%28data_structure%29https://en.wikipedia.org/wiki/Graph_databasehttps://en.wikipedia.org/wiki/Distributed_transactionhttps://en.wikipedia.org/wiki/Two-phase_commit_protocolhttps://en.wikipedia.org/wiki/Two-phase_commit_protocolhttps://en.wikipedia.org/wiki/Middleware_%28distributed_applications%29https://en.wikipedia.org/wiki/Heterogeneous_database_systemhttps://en.wikipedia.org/wiki/Federated_database_systemhttps://en.wikipedia.org/wiki/Embedded_databasehttps://en.wikipedia.org/wiki/Distributed_databasehttps://en.wikipedia.org/wiki/Dataloghttps://en.wikipedia.org/wiki/Logic_programminghttps://en.wikipedia.org/wiki/Deductive_databasehttps://en.wikipedia.org/wiki/Data_mininghttps://en.wikipedia.org/wiki/ACNielsenhttps://en.wikipedia.org/wiki/Universal_Product_Codehttps://en.wikipedia.org/wiki/Data_warehousehttps://en.wikipedia.org/wiki/Open_APIhttps://en.wikipedia.org/wiki/Web_browserhttps://en.wikipedia.org/wiki/Cloud_computinghttps://en.wikipedia.org/wiki/Cloud_databasehttps://en.wikipedia.org/wiki/Database_trigger


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An array DBMS is a kind of NoSQL DBMS that allows to model, store, and retrieve (usually

large) multi-dimensional arrays such as satellite images and climate simulation output.

In a hypertext or hypermedia database, any word or a piece of text representing an object,

e.g., another piece of text, an article, a picture, or a film, can be hyperlinked to that object.

Hypertext databases are particularly useful for organizing large amounts of disparateinformation. For example, they are useful for organizing online encyclopedias, where users

can conveniently jump around the text. The World Wide Web is thus a large distributed

hypertext database.

A mobile database can be carried on or synchronized from a mobile computing device.

Operational databases store detailed data about the operations of an organization. They

typically process relatively high volumes of updates using transactions. Examples include

customer databases that record contact, credit, and demographic information about a business'

customers, personnel databases that hold information such as salary, benefits, skills dataabout employees, enterprise resource planning systems that record details about product

components, parts inventory, and financial databases that keep track of the organization's

money, accounting and financial dealings.

A parallel database seeks to improve performance through parallelization for tasks such as

loading data, building indexes and evaluating queries.

Probabilistic databases employ fuzzy logic to draw inferences from imprecise data.

Real-time databases process transactions fast enough for the result to come back and be acted

on right away.

Spatial database can store the data with multidimensional features. The queries on such data

include location based queries, like "Where is the closest hotel in my area?".

A temporal database has built-in time aspects, for example a temporal data model and a

temporal version of SQL. More specifically the temporal aspects usually include valid-time

and transaction-time.

A terminology-oriented database builds upon an object-oriented database, often customized

for a specific field.

An unstructured data database is intended to store in a manageable and protected way diverse

objects that do not fit naturally and conveniently in common databases. It may include email

messages, documents, journals, multimedia objects, etc. The name may be misleading since

some objects can be highly structured. However, the entire possible object collection does not

fit into a predefined structured framework. Most established DBMSs now support

unstructured data in various ways, and new dedicated DBMSs are emerging.

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Design and modeling of DBMS in Educational Institutions

Databases are widely used. Here some representative applications:

Banking: 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

Among these applications here we will focus on the database system of educationalinstitutions such as university where add new students, instructors, and courses; Register

students for courses, and generate class rosters; assign grades to students, compute grade

point averages (GPA) and generate transcripts etc. can be done using DBMS.

Here we will use MYSQL language and XAMPP software to demonstrate the practical

applications of DBMS in educational institutions. For example we will create a database of

ten students including two tables where

Table1: Student

Contains the information about student ID, their name, Admission session, in which semester

they are registered and the total number of courses they have taken.

Table2: Course

Contains the information about the courses taken by these ten students such as course name,

course code.

Once we create these tables we can able to make any query regarding these students course

and admission session using relational model. We can also update or add or delete any

information. The details of the process are explained below:

At first we have to run the XAMPP software and browse http://localhost/phpmyadmin/ using

internet explorer browser. Here we will create a database named ―Student‖. After that create

Student and Course table using MYSQL command.

http://localhost/phpmyadmin/http://localhost/phpmyadmin/


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Figure 5: The ―Student‖ Table


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Figure 6: The ―Course‖ Table

Now we want to Show records from Course Table. The command will be:

SELECT * FROM `Course` WHERE `S_Id` = '20017';


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Output:

Figure 7: Showing all data from "course" Table

In this figure we can see the entire course Name, Course Code taken by Student ID: 20017

Now we want to Show records from both Student and Course table

SELECT Student.S_ID, FirstName, CourseName, CourseCode

FROM Student, Course

where Student.S_Id= Course.S_Id and Student.S_Id= '20017'


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OUTPUT:

Here all the Information about the course name, course code and students’ Name of is shown.

If we want to know how many students among these ten students have taken Database

Management Systems then the command will be:

SELECT Student.S_ID, Name, CourseName, CourseCode

FROM Student, Course

where Student.S_Id= Course.S_Id and CourseCode= 'EMIS-520'


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Modification of the Database – Deletion

Delete all students who have taken Database Management Systems Course

delete from Course

where CourseName= 'Database Management Systems';

Then all the students who have taken 'Database Management Systems' will be deleted.

Modification of the Database – Insertion

Again we can insert any required data using the following command:

INSERT INTO `Student` (`S_Id`, `Name`, `AdmissionSession`,

`Semester`, `TotalCourses`)

VALUES ('20100', 'ABC', '2014-2015', 'Summer', '3');


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Modification of the Database – Updates

In certain simulations, we may wish to change a value in a tuple without changing all values

in the tuple. For this purpose Update statement can be used. As we could for insert and delete,

we can choose the tuples to be updated by using a query.


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Advantages of the DBMS

The DBMS serves as the intermediary between the user and the database. The database

structure itself is stored as a collection of files, and the only way to access the data in

those files is through the DBMS. The DBMS receives all application requests and

translates them into the complex operations required to fulfill those requests. The DBMS

hides much of the database’s internal complexity from the application programs and

users. The different advantages of DBMS are as follows. Improved data sharing. The

DBMS helps create an environment in which end users have better access to more and

better-managed data. Such access makes it possible for end users to respond quickly to

changes in their environment.

Improved data security. The more users access the data, the greater the risks of data

security breaches. Corporations invest considerable amounts of time, effort, and money

to ensure that corporate data are used properly. A DBMS provides a framework for better enforcement of data privacy and security policies.

Better data integration. Wider access to well-managed data promotes an integrated view

of the organization’s operations and a clearer view of the big picture. It becomes much

easier to see how actions in one segment of the company affect other segments.

Minimized data inconsistency. Data inconsistency exists when different versions of the

same data appear in different places. For example, data inconsistency exists when a

company’s sales department stores a sales representative’s name as ―Bill Brown‖ and the

company’s personnel department stores that same person’s name as ―William G.

Brown,‖ or when the company’s regional sales office shows the price of a product as$45.95 and its national sales office shows the same product’s price as $43.95. The

probability of data inconsistency is greatly reduced in a properly designed database.

Improved data access. The DBMS makes it possible to produce quick answers to ad hoc

queries. From a database perspective, a query is a specific request issued to the DBMS

for data manipulation — for example, to read or update the data. Simply put, a query is a

question, and an ad hoc query is a spur-of-the-moment question. The DBMS sends back

an answer (called the query result set) to the application. For example, end users, when

dealing with large amounts of sales data, might want quick answers to questions (ad hoc

queries) such as:- What was the dollar volume of sales by product during the past six

months?- What is the sales bonus figure for each of our salespeople during the past three

months?- How many of our customers have credit balances of $3,000 or more?

Improved decision making. Better-managed data and improved data access make it

possible to generate better-quality information, on which better decisions are based. The

quality of the information generated depends on the quality of the underlying data. Data

quality is a comprehensive approach to promoting the accuracy, validity, and timeliness

of the data. While the DBMS does not guarantee data quality, it provides a framework to

facilitate data quality initiatives.

Increased end-user productivity. The availability of data, combined with the tools that

transform data into usable information, empowers end users to make quick, informed


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decisions that can make the difference between success and failure in the global

economy.

Disadvantages of Database

Although the database system yields considerable advantages over previous data management

approaches, database systems do carry significant disadvantages. For example:

Increased costs. Database systems require sophisticated hardware and software and

highly skilled personnel. The cost of maintaining the hardware, software, and

personnel required to operate and manage a database system can be substantial.

Training, licensing, and regulation compliance costs are often overlooked when

database systems are implemented.

Management complexity. Database systems interface with many different

technologies and have a significant impact on a company’s resources and culture. Thechanges introduced by the adoption of a database system must be properly managed

to ensure that they help advance the company’s objectives. Given the fact that

database systems hold crucial company data that are accessed from multiple sources,

security issues must be assessed constantly.

Maintaining currency. To maximize the efficiency of the database system, you must

keep your system current. Therefore, you must perform frequent updates and apply

the latest patches and security measures to all components. Because database

technology advances rapidly, personnel training costs tend to be significant.

Vendor dependence. Given the heavy investment in technology and personneltraining, companies might be reluctant to change database vendors. As a consequence,

vendors are less likely to offer pricing point advantages to existing customers, and

those customers might be limited in their choice of database system components.

Frequent upgrade/replacement cycles. DBMS vendors frequently upgrade their

products by adding new functionality. Such new features often come bundled in new

upgrade versions of the software. Some of these versions require hardware upgrades.

Not only do the upgrades themselves cost money, but it also costs money to train

database users and administrators to properly use and manage the new features.


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Conclusion

Education system is not only a social system, but the only way to educate manpower for other

social systems, such as legal system, economy, policy, security, and others, and the basis

system to transmit common culture to the next generations to provide eternity of nation as

well. The success of this system is the success of the community. The managers who are the

cornerstones of this success, should be chosen by systematic approach, well trained,

developed, continuity should be provided. They should keep track of our era and follow the

changes and developments to train next generations to realize the improvement and better

quality. Knowing this history, where are DBMS used today? Would you believe everywhere?

That's right - everything from educational sectors, banking transactions to online auctions -

anything that deals with data and information is using some sort of database management

system. And as technology grows, as more businesses and consumers get online for various

reasons, you can expect more and more usage.


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References

Database System Concepts by Abraham Silberschatz, Henry F.Korth, S.Sudarshan

http://www.comphist.org/computing_history/new_page_9.htm

http://www.brighthub.com/internet/web-development/articles/109527.aspx

https://en.wikipedia.org/wiki/Database

Architecture of a Database System by Joseph M. Hellerstein, Michael Stonebraker

and James Hamilton

http://www.tutorialspoint.com/dbms/dbms_overview.htm
http://www.comphist.org/computing_history/new_page_9.htmhttp://www.brighthub.com/internet/web-development/articles/109527.aspxhttps://en.wikipedia.org/wiki/Databasehttps://en.wikipedia.org/wiki/Databasehttp://www.brighthub.com/internet/web-development/articles/109527.aspxhttp://www.comphist.org/computing_history/new_page_9.htm

term paper on dbms

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