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Data Cube Representation for Vehicle Insurance Policy System

by Narander Kumar, Vishal Verma, Vipin Saxena
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 1
Year of Publication: 2012
Authors: Narander Kumar, Vishal Verma, Vipin Saxena
10.5120/9243-3372

Narander Kumar, Vishal Verma, Vipin Saxena . Data Cube Representation for Vehicle Insurance Policy System. International Journal of Computer Applications. 58, 1 ( November 2012), 1-4. DOI=10.5120/9243-3372

@article{ 10.5120/9243-3372,
author = { Narander Kumar, Vishal Verma, Vipin Saxena },
title = { Data Cube Representation for Vehicle Insurance Policy System },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 1 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number1/9243-3372/ },
doi = { 10.5120/9243-3372 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:01:22.843036+05:30
%A Narander Kumar
%A Vishal Verma
%A Vipin Saxena
%T Data Cube Representation for Vehicle Insurance Policy System
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 1
%P 1-4
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

On-Line Analytical Processing (OLAP) systems have a strong focus on the interactive analysis of data and typically provide extensive capabilities for visualizing the data and generating summary statistics. Most of the data sets can be represented as a table, where each row is an object and each column is an attribute. Data cube represents the multidimensional data with all possible aggregates. The three dimensional data cubes represent the different attributes entirely controlled with the help of objects. In general, a data cube is generalization of statistical terminology as a cross-tabulation. In the present work, authors have designed a framework of OLAP data cube to analyze the Vehicle Insurance Policy (VIP) system to identify the entity, which is highly preferred by the customer. The study describes a methodology with OLAP data cube and pivot table as well as a correlation technique which represents strong relationship among the data attributes. Tables and graphs are designed for the sample database of the Vehicle Insurance Policy System

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Index Terms

Computer Science
Information Sciences

Keywords

OLAP OOMD Data Cube Pivot Table Correlation Coefficient

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