International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 5 Issue 4, April 2016 | Popularity: 6.3 / 10


     

Data Analysis in Business Intelligence for Mathematical Prediction of Online Sale

Varsha B. Saknure, D. V. Jadhav


Abstract: Business-intelligence is an effective means of improving the decision making within an organization applied to profit making private companies. The online purchase and trading data available on website can be a key reference to analyze for the decision making in small scale business. The electronics product market is more volatile in nature and is having frequent variation. Such behavior of product variation has increases the risk of over inventory towards the dealers. The effective analysis of behavior of the product sale over the year can be set as a foundation for decision making. The recent BI tools are used to analyze the data to develop the report generation of the sale. These reports are studied to develop the thumb rules with respect to the variation of sale. Such thumb rule is designed to use as a knowledge base in developing a mathematical model for the predictions of sales behavior of electronics products. The Prestashop based sales module is used along with the BI tool Pentaho for the development of sales report in this paper. The MATLAB is used to develop the mathematical prediction.


Keywords: Business Intelligence, Sale of Electronics products, Sales Module, Pentaho, Mathematical Prediction


Edition: Volume 5 Issue 4, April 2016


Pages: 2020 - 2024


DOI: https://www.doi.org/10.21275/NOV163091



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Varsha B. Saknure, D. V. Jadhav, "Data Analysis in Business Intelligence for Mathematical Prediction of Online Sale", International Journal of Science and Research (IJSR), Volume 5 Issue 4, April 2016, pp. 2020-2024, https://www.ijsr.net/getabstract.php?paperid=NOV163091, DOI: https://www.doi.org/10.21275/NOV163091



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