Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Reseach Article

Application of Business Intelligence using Machine Learning Approach

by Zainab Pirani, Anuja Marewar, Zainab Bhavnagarwala, Madhuri Kamble
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 165 - Number 13
Year of Publication: 2017
Authors: Zainab Pirani, Anuja Marewar, Zainab Bhavnagarwala, Madhuri Kamble
10.5120/ijca2017914131

Zainab Pirani, Anuja Marewar, Zainab Bhavnagarwala, Madhuri Kamble . Application of Business Intelligence using Machine Learning Approach. International Journal of Computer Applications. 165, 13 ( May 2017), 28-31. DOI=10.5120/ijca2017914131

@article{ 10.5120/ijca2017914131,
author = { Zainab Pirani, Anuja Marewar, Zainab Bhavnagarwala, Madhuri Kamble },
title = { Application of Business Intelligence using Machine Learning Approach },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 165 },
number = { 13 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume165/number13/27731-2017914131/ },
doi = { 10.5120/ijca2017914131 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:25.442524+05:30
%A Zainab Pirani
%A Anuja Marewar
%A Zainab Bhavnagarwala
%A Madhuri Kamble
%T Application of Business Intelligence using Machine Learning Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 165
%N 13
%P 28-31
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As the online marketing businesses are expanding it is difficult for e-commerce organizations to keep a track of the products in its inventory[1]. The manual process is a slow process and each and every product needs to be scanned, recorded and then be stored. This probably leads to wasting much of their time switching between applications to track shipment, to receive payment, to manage orders and to view customer details. To solve the problems faced by various organizations our paper proposes ‘Inventory Management Software’- online inventory management software that keeps track of stock levels, helps to manage orders which reduces the trouble they face by using multiple applications. The inventory management software is a useful and mandatory tool which makes use of business intelligence to provide organizations with a complete overview of their inventory just by looking at its dashboard. Various graphs are generated by this software which indicate the stock levels on daily, monthly or weekly basis. It’s real-time inventory dashboard to help optimize sales and inventory levels to get critical insights of the business whenever required. Thus, software is used for analytics purpose using various machine learning algorithms to run an efficient business.

References
  1. W Xu, D.P.Song,  Roe M. 2010 Supply chain performance improvement using vendor Management Inventory Strategy, 2010 IEEE International Conference on Industrial Engineering and Engineering Management.
  2. Malek Sarhani, AbdellatifAfia EI. 2014 Intelligent system based support vector regression for Supply chain demand forecasting, IEE Second World Conference on Complex Systems (WCCS).
  3. Fang Tu, Sudipto, Ghoshal Jianhui, Luo Gautam, Biswas Sankaran, Mahadevan Link Jaw, Kelly N. 2007 PHM Integration with Maintenance and Inventory Management System, IEEE Aerospace Conference.
  4. Yoo P.D., M.H. Kim, Jan T. 2005 Machine Learning Techniques And Use of Event Information for Stock Market Prediction on: A Survey and Evaluation, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).
  5. Pradip Kumar 2010 Decision tree based demand forecasts for improving inventory Performance, IEEE International Conference on Industrial Engineering And Engineering Management.
  6. https://quickbooks.intuit.com/inventory-management/
  7. https://www.jazva.com/features/inventory-management
Index Terms

Computer Science
Information Sciences

Keywords

Business Intelligence E-commerce Inventory Management Software Machine Learning