Proceeding of

NCAICN National Conference 2013

(NCAICN-2013)

on

Advances in

Computing & Networking

as

A Special Issue of

International Journal of Computer Science and Applications

(ISSN:0974-1011)

Patron

Hon. Shri Sundeepji Meghe

(Chairman, Vidarbha Youth Welfare Society, Amravati)

 

Advisor

Dr. V.T. Ingole (FIE, FIETE, Professor Emeritus)

 

Organizing Committee

Chairman

Dr. D.T. Ingole (FIE, FIETE)

(Principal PRMIT & R, Badnera and  Chairman IEI  Amravati Center).

Secretary

 Er. A.W. Jawanjal

(Honorary Secretary IEI, Amravati Center)

Conveners

Dr. G.R. Bamnote ((FIE, FIETE)

(H.O.D. Computer Science & Engineering)

Dr. A.S. Alvi (MIE)

(H.O.D. Information Technology))

Prof. Mrs. M.D. Ingole (FIE.MIETE)

(H.O.D. Electronics & Telecommunication)

Coordinators

Prof. S.V. Dhopte ((FIE, FIETE)

Prof. Ms. V.M. Deshmukh (FIE, FIETE)

Dr. S.W. Mohod  (FIE,FIETE)

Co-Coordinators

Dr. S.R. Gupta (MIE, MIETE)

Prof. S.V. Pattalwar ((FIE, FIETE)

Prof. M.D. Damahe

Members

Prof. Mrs. M.S. Joshi                

Dr. S.M. Deshmukh

Prof. V.U. Kale

Prof. S.S. Kulkarni

Prof. Ms. R.R. Tuteja

Prof. Ms. J.N. Ingole

Prof. V.R. Raut

Prof. C.N. Deshmukh

Prof. Ms. M.S. Deshmukh

Prof. S.P. Akarte

Prof. Mrs. A.P. Deshmukh

Prof. Mrs. S.S. Sikchi

Prof. N.N. Khalsa

Department of Information and Computer Science and Engineering

Prof. Ram Meghe Institute of Technology and Research, Badnera Distt. Amravati

 

Editor

Prof. K. H. Walse

M.S.India
 

 

 

   
   
   
   
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
  
IJCSA ISSN: 0974-1011 (Online) >>    
Title:

Data Mining and Warehousing

Author:
 Mr. Shital S. Agrawal and Prof. Ms. R. R. Tuteja
 
Abstract

Data mining,  the extraction of  hidden  predictive information   from   large  database,   is   a   powerful   new technology with great potential to  help Companies focus on the  most important  information in their  data warehouses. Data  Mining  tools  predicts  future  trends  and  behaviors, allowing   business   to   make   proactive   knowledge-driven decisions.  The automated,  prospective  analysis  offered  by data   mining   move   beyond  the analysis   of   past   events provided by retrospective tools  typical  of decision support systems. Data Mining  tools can answer business questions that traditionally  were too time consuming to resolve. Data Mining  techniques can be implemented rapidly on existing software and hardware platforms to enhance the  value of existing information resources, and can be  integrated with new  products  and  system  as  they   are  brought  online. Analyzing data  can  provide   further  knowledge  about  a business by going beyond the data explicitly stored to derive knowledge about the business.

©2013 International Journal of Computer Science and Applications 

Published by Research Publications, India