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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
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← Back to VOLUME 6, ISSUE 8, AUGUST 2017

Data Mining Techniques for Business Intelligence and Its Applications – A Survey

Mr. A. Venugopal, Jisha. P

DOI: 10.17148/IJARCCE.2017.6833

Abstract: This paper deals with the data mining approaches and tools used for the business intelligence and inventory analysis. It describes the use of data mining approaches in business intelligence (BI), which coupled with data warehouse to employ data mining technology to provide accurate and up-to-date information for effective decision support system in business. The list of methodologies used in the literature is analyzed. This will help to provide out-of-stock forecasts at the store/product level. The inventory management and supply chain management using data mining techniques will improve the business by providing effective demand analysis, demand forecasting and appropriate decision support for the business. This survey concludes the further improvements which can improve the accuracy in demand analysis and forecasting in the inventory and supply chain management system. This also provides the challenges of those processes in terms of data size and uncertain business environments.



Keywords: Inventory Management, Data Mining, Big Data, Neural Networks, Hybrid Intelligent Systems, Demand Forecasting.

How to Cite:

[1] Mr. A. Venugopal, Jisha. P, β€œData Mining Techniques for Business Intelligence and Its Applications – A Survey,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2017.6833