Dbms Slides - Uic - 2

8/2/2019 Dbms Slides - Uic - 2

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2006 Prentice Hall, Inc. 5 1

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Amity Business School

DBMS

DATABASE MANAGEMENT SYSTEM

& ITS COMPONENTS


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What Exactly Is DBMS?

A database management system (DBMS)is an extremely complex set of software

programs that controls the Organization,Storage & Retrieval of Data in a database& also controls Its security & Integrity.


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DATABASE

It is a complete file system that uses a particular file organization to facilitate

rapid & simultaneous updating of related records, also providing easy & rapidaccess to all stored data.


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TYPES OF DATABASE


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WHAT LED TO THEDEVELOPMENT OF DBMS

The problem arising from the traditional file environment approachbrought forward the development of DBMS i.e.

DATA REDUNDANCY

DATA INCONSISTENCY

DATA ISOLATION

DATA INTEGRITY


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DBMS provided solutions by eliminating these problems and providingwith the following advantages :

1. Reduced complexity of the organizations information systems

environment.

2. Reduced data redundancy & inconsistency

3. Improved maintenance costs.

4. Increased access & availability of data & information.

MAJOR COMPONENTS OF DBMS


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Amity Business SchoolMAJOR COMPONENTS OF DBMS

DATA MODEL : It defines theway data are conceptually

structured.

TYPES OF DATA MODEL

A) Hierarchical Database Model :

In this particular model, the database is arranged logically inan inverted tree pattern such thateach database has only one

owner. For example,

Management hierarchy in anorganization

MANY EMPLOYEES BUT ONE MANAGER AT EACH LEVEL :

Searching is fast & efficient in hierarchical database model.


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c) Relational Database Model :

It is based on the simple concept of tables in order to

capitalize on characteristics of rows & columns ofdata. In a relational database, these tables are calledrelations, besides this, each row of data is equivalentto a record and each column of data is equivalent toa field.

NAME TITLE AGE DIVISIO

Smith A. Dir. Accounting 43 CHINA

Jones W. Dir. Total QualityManagement

32 STERNWARE

Lee J. Dir. I.T. 46 CHINA

Durham K. Manager, Production 35 STERNWARE




EMERGING DATA MODELS

Object-Oriented Database Model :

It is a recent development in database models. Thecentral idea is that of an object i.e. a small amount

of data encapsulated with all the data needed inorder to perform an operation with that data.




Multidimensional Database Model :

In this model, the data are intimately related & can be viewed & analyzed from different perspectives or dimensions. These dimensionsrepresent the primary views of business data, for

example,

SALE DATA(Dimensions)

Product Geography Time

It represents sales of a specific product, in a

specific market, at a particular time.




MultidimensionalModel

Dealership

Actual Salesfor Blue &Sports acrossdealers

Sales Volumes




Data Definition Language:

The data definition language defines what types of

information are in the database & how they will bestructured. It is essentially the link between the logicaland physical structures of the database.

LOGICAL : the way the user views data

PHYSICAL : the way the data is physically stored.

It defines the physical characteristics of each record.

a) the fields within the record

b) Each fields data type

c) Each fields length & logical name




Data Manipulation Language :

The data manipulation language allows users toretrieve, sort, display & delete the contents of a database & for this very purpose QUERYLANGUAGES are used.

QUERY LANGUAGE :

A query language is a set of commands for creating, updating & accessing data from adatabase.

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One of the most popular forms of query language is SQL orSTRUCTURED QUERY LANGUAGE . SQL offers the ability to

perform complicated searches with relatively simple statement

such as

SELECT- to specify a desired attribute.

FROMto specify the table to be used

WHEREto specify conditions to apply in the query.For example,

SELECTName, Address, City State, PIN

FROMCustomer

WHERE State = MH

The result would be a list of the names & addresses of allcustomers located in Maharashtra.

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Data Dictionary :

The data dictionary stores definitions of data elements

i.e. fields & data characteristics such as individuals, business functions programs & reports that use the data elements as well as the physical representation,responsible parties in the organization i.e. data owners

& security. Because the data dictionary providesstandard definitions for all data elements, the potential for data inconsistency is reduced. In addition, it provides for faster program development because

programmers do not have to create new data names.Data dictionaries also make it easier to modify data &information.

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BENEFITS OF DBMS TO CORPORATEWORLD

Data Warehouses :

A data warehouses is a relational or multidimensionalDBMS designed to support management decision making.

Data warehouses are oriented around the major business subjects of the enterprise, such as customer, vendor, product or activity. The data in the warehouse are stored in a single, agreed upon format which provides business users with a Customer centre view of the

companys heterogeneous data.

It provides added value to the companys customers byallowing them to access better information.

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Data Marts :

A data-mart is a scaled-down version of a data

warehouse that focuses on a particular subject area. Itis designed to support the unique business requirements of a specific department or businessprocess. A company can have many data marts, each

focused on a subset of the entire firm. Because of its reduced scope, a data mart takes less time to build, costs less and is less complex than anenterprise data warehouse. Therefore, a data mart is

appropriate when a company needs to improve data access in a targeted area, such as the marketingdepartment.

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Data Mining :

Data mining provides a means of extracting

previously unknown, predictive information from

the base of accessible data in data warehouses.

Data mining tools use sophisticated, automated

algorithms to discover hidden patterns,

correlations & relationships among organizational

data. These tools are used to predict future trends

& behaviors, allowing businesses to makeproactive, knowledge driven decisions.

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For example, one typical predictive problems is

targeted marketing. Data mining can use data on

past promotional mailings to identify the targets

most likely to maximize the return on the

companys investment in future mailings.



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