A CASE STUDY ON DATA MINING AND DATA WAR (1)

GADL Journal of Inventions in Computer Science and Communication Technology (JICSCT)
ISSN(O): 2455-5738
Volume 3 – Issue 4,-July-Aug 2017

A CASE STUDY ON DATA MINING AND DATA WAREHOUSE

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Richa Mewara , Sarvesh Singh
Dept. of Computer Science & Engineering, JVWU Jaipur

ABSTRACT
A data warehouse provides us generalized and
consolidated data in multidimensional views. A
data warehouse also provides us online Analytical
Processing tools. This analysis results in database
generalization and data mining. In this no frequent
updating done in a data warehouse. It is use their
data to take strategic decisions. It helps in the

integration of diversity of applications systems.

This paper shows information and new application
in data mining and data warehouse as well as the
advantage of data mining and data warehouse the
purpose of data mining and data warehouse to
make decision making system in any field for
business and organization. This project for how the
business will organize in marketing field and what
are the advantage or disadvantage for data mining
and data warehouse it represent the new techniques
in the top of the market for accessing and increase
the value for the database. Thus the paper shows
that what is data mining and data warehouse and
how is use in market and what all are the advantage
for market value. It is familiar that the strategic
level of decision usually does not use business
information on a daily basis but instead, derivative
data from specific time. It is necessary in decisionmaking process to consider the large amounts of
database so that the quality of decision-making is

satisfied. Data Warehouse and Data Mining
concept are any as a good base for business
decision-making.

APPLICATION OF DATA
WAREHOUSE
BANKING INDUSTRY
Bank Intelligence is a method of storing and
presenting and accessing of business data so that
anyone in the bank can quickly and easily access
data and asks questions of accurate and timely data.
In a bank networks, hundreds of millions of
customer database records are generated daily. Data
Warehouse provides a consolidated database view
of the past transactions and is not useful without a
proper strategies or view to convert that into
information.

Keywords:

Data Mining, Data Warehouse,
Database, Information.

FINANCE INDUSTRY
INTRODUCTION TO DATA
WAREHOUSE

A financial data warehouse using the latest
technologies can increase the quality of our data
and help us to gain insights into customer
behaviour. Clients often improve the effectiveness
of their marketing campaigns and loyalty programs
as a result of these new insights.Our financial
analytics services are business-driven and our
experts spend time establishing our individual
requirements and task. Our consulting services help
financial businesses to:

A data warehouse is a database which use for kept
the data and large amount of information from

organization’s operational database. That user can
easily access and use the data from data warehouse.
A business organization’s wants to access or
analyze the previous data or feedback on any
database such as product, a supplier, or any other
data then the executive will have no database
available to analyze because the previous data has
been updated due to transactions.





Make decisions more effectively and easy
to access.
Bring new products onto the market.
A growing number of regulations.

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GADL Journal of Inventions in Computer Science and Communication Technology (JICSCT)
ISSN(O): 2455-5738
Volume 3 – Issue 4,-July-Aug 2017

GOVERMENT AND EDUCATION

APPLICATION OF DATA MINING
RETAIL INDUSTRY

The objective of the Data Warehouse is to enable
easy access to accurate and integrated government
database for better and faster decision making and
more efficient decisions purposes. The Government
Data Warehouse will be a single data with a
subject-centric approach, in order to provide a view
of Service data, optimised for reporting and
analysis. Educational institutions have developed

into large businesses in and of themselves. This
change has resulted in more business-like
management of these institutions as well. To gain
an appreciation of how the data warehousing
process can benefit institutions of higher education,
we can take the many example of the benefits
manufacturing and sales organizations have
enjoyed from this process and apply them to the
educational setting. This application will help to
provide more clear understanding of the value data
warehousing can provides to higher education
institutions and many others .

Retail industry collects large amount of database
and information on sales and customer shopping
history. The quantity and quality of data and
information collected continues to rapidly,
especially due to the increasing ease, availability
and popular the business conducted on web, or
retail industry provides a rich source for data

mining. Retail database mining can help identify
customer behaviour, discover customer shopping
trends, improve the quality of customer service and
patterns, achieve better customer retention and
satisfaction and feedback, enhance goods
consumption ratios design more effective goods
transportation and distribution policies and reduce
the cost of business.

BIOLOGICAL DATA ANALYSIS
Data mining techniques which designed to handle
such challenging data analysis problems, And with
real life applications how biologists and clinical
scientists can employ data mining to enable them to
make meaningful strategy from a wide array of
heterogeneous data from molecular biology and
clinical domains.
 Data produced by different labs need to be
integrated and for accessing.
 Data mining can be used to perform data

cleaning and
integration, object reconciliation to merge
heterogeneous databases.
 Build phylogenetic trees.
 Similarity search.
 Difference search.
 3D structure of proteins heavily affects
their
Functionalities.
 Prediction of protein structures.
 Discovery of regularities.

INTRODUCTION OF DATA MINING

Data mining the extraction of hidden predictive
information from large databases Is a powerful new
technology with great potential to help companies
focus on the most important information and
database in their data warehouses. A data mining
tools predict future trends and behaviours and

database, allowing businesses to make knowledgedriven decisions.
The automated prospective analyses offered by data
mining move the analyses of past and present
events provided by retrospective tools typical of
decision support systems. Data mining tool can
answer business questions that traditionally were
too time consuming to resolve. Databases for
hidden patterns, finding predictive information
those experts may miss because it lies outside their
expectations. Data mining process is the result of a
long process of research and accessing the
database, product development and decision
making system.
This evolution begin when business database was
first stored on computers, continued with
improvements in database access, and more
recently, generated .

CRIME INVESTIGATION
The growing insecurity challenges are of great

concern to everyone and everywhere effort must be
employed to these security issues. Using the
proposed data mining profiler model, our work

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GADL Journal of Inventions in Computer Science and Communication Technology (JICSCT)
ISSN(O): 2455-5738
Volume 3 – Issue 4,-July-Aug 2017

distinguishes between information related threats
and non-information related security threats.
Information related threats are essentially attacks
on computers and networks. They are threats that
damage electronic information and data. Noninformation related terrorist threats include terrorist
attacks, bombing, shooting and, vandalism,
kidnapping, setting property on fire. The questions

asked by all stakeholders are can the security
agencies and their strategies fight the noninformation related security threats. Do these
agencies have appropriate Information Technology
Infrastructure in place for the purpose of
information gathering, sharing, dissemination, and

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decision making.The circumstances of humans
social life, makes it vital to encounter a
phenomenon known as crime. So we always need
to the knowledge of crime analysis as an efficient
combating tool. Crime analysis basically includes
leveraging a systematic approach for identifying,
discovering and sometimes predicting crime
incidents. The input of a crime analysis system is
consisted of data and information assigned to crime
variables and the output includes the answer to
investigative and analytical questions, knowledge
extraction and finally visualization of the results.

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COMPARISON BETWEEN DATA
MINING AND DATA WAREHOUSE
#
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2.

3.

4.

Data Mining
Data Mining is a
set of techniques
used to search,
retrieve
and
analyze data from a
data warehouse.
Data Mining is
Used in a wide
variety of contexts
in fraud detection,
as an aid in
marketing
campaigns.
Data Mining is a
method
for
comparing
large
amount of data for
the purpose of
finding patterns.
Data Mining is

Data Warehouse
Data Warehouse is
about the storing of
analytical data in a
structure suitable for
data mining.

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Data Warehouse can
be said to be the
process of centralizing
or aggregating data
from multiple sources
into one common
repository.
Data Warehouse is the
central repository for
the data of several
business system in an
enterprise.
Data

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intended for users
who
are
statistically
inclined
these
analysts look for
patterns hidden in
data to extract
using
statistical
models.
Data Mining is the
process of finding
patterns in a given
data set these
patterns can often
provide meaningful
and insightful data
to whoever is
interested in that
data.
Data Mining is
specific in data
collection.

Data Mining is
typically done by
business users with
the assistance of
engineers.
Data Mining is a
process that apply
algorithms to
extract knowledge
from the data that
we even don’t
know exist in the
database.
A Data Mining one
can use this data to
generate different
reports like profits
generated etc.
Data Mining is the
process of
extracting
meaningful data
from that database.

users, on the other
hand to be data
experts who analyze
by
business
dimensions directly.

Data Warehouse can
be said to be the
process of centralizing
or aggregating data
from multiple sources
into one common
repository.

Data Warehouse is a
tool to save time and
improve efficiency by
brining data from
different location from
different areas of the
organization together.
Data Warehouse is
typically a process
done exclusively by
engineers.
Data Warehouse is an
environment where
the data of an
enterprise is gathering
and stored in a
aggregated and
summarized manner.
A DWH of a company
stores all the relevant
information of
projects and
employees.
Data Warehouse is the
process of compiling
and organizing data
into one common
database.

Warehouse

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GADL Journal of Inventions in Computer Science and Communication Technology (JICSCT)
ISSN(O): 2455-5738
Volume 3 – Issue 4,-July-Aug 2017

11.https://www.slideshare.net/wikramanayake/appl
ication-of-data-warehousing-data-mining-toexploitation-for-supporting-the-planning-of-highereducation-system-in-sri-lanka.

CONCUSION
This paper shows the Introduction of data mining
and data warehouse. And their application Based
on the some real life problems we can conclude
that Data ware house offers a flexible solution to
the user to access the data, who can use many
application and task for data mining as well as data
ware house in many fields of education and in more
many field. A data warehouse project can be very
difficult. Analysis of the success of the data
warehouse project is done considering the financial
benefits against the investment. Since most of the
educational institutes are nonprofits organizations
and services oriented data, the evaluation of the
usefulness of the data warehouse can be done on
the basis of its ability to meet user’s requirements
in many other fields.

12.http://whatisdbms.com/12-applications-of-datawarehouse.
13.http://www.1keydata.com/datawarehousing/data
-warehouse-definition.html.
14.http://searchsqlserver.techtarget.com/definition/
data-warehouse.
15.https://www.tutorialspoint.com/dwh/dwh_data_
warehousing.htm.
16.https://docs.oracle.com/cd/B10500_01/server.92
0/a96520/concept.htm.

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