International Journal of Scientific and Research Publications

IJSRP, Volume 2, Issue 10, October 2012 Edition [ISSN 2250-3153]

Architecture of an Automated CBA System Using ERP Model
      Shweta Tiwari, Prof. Sapna Choudhary
Abstract: In this paper , a model is proposed which integrates the database, customer queries, transactions, and all other specifications used in ERP systems, then use enhanced & latest data mining techniques to integrate decision making and forecast flows. The proposal of the paper is based on the data mining effects using ERP framework. By using the various properties of ERP’s and background we collect the data from central database in cluster format which is based on the action taken against the queries generated by the customers. Furthermore, the clustered data used by ARM Algorithm to extract new rules and patterns for the enhancement of an organization. This is a complete architecture of data mining applications on ERP framework to find out the answers of upcoming queries. This will make the best association between the customers and organization. It act as a base for a CRM system as it permits the company itself to recommend other products by e-mail. The model is basically consist of three layers 1) CRM 2) ERP 3) KNOWLEDGE DISCOVERY. Here the third layer is the proposed layer, since the Knowledge discovery can be defined as the extraction of contained, hidden and useful information from the large database. So in this presented model this layer also deal with the central database containing data collected from any department of ERP and CRM layers. Since customer’s queries contain unlimited attributes and characteristics of data. By utilizing the benefits of third layer in the proposed model we used enhanced variation of Apriori algorithm i.e distributed cba Algorithm for effective and high-quality results.

Reference this Research Paper (copy & paste below code):

Shweta Tiwari, Prof. Sapna Choudhary (2018); Architecture of an Automated CBA System Using ERP Model; Int J Sci Res Publ 2(10) (ISSN: 2250-3153).
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