Constraint Mining in Business Intelligence: A Case Study of Customer Churn Prediction

Abstract

In the era of digital technologies, most enterprises have collected huge amount of data in an electronic form. Business intelligence technology has emerged as a tool to support information summarization, pattern extracting, knowledge discovery, and other knowledgerelated tasks. The main part of most business intelligence software is the data mining engine to analyze and report relationships that exist in the stored data. Visualization tools are created to help data analysts easily explore the induced information. For extremely large amount of data stored in the data warehouse and data marts, simply explore information and knowledge through the visualize tool is not possible. We thus propose to put more constraints in the data mining engine of the BI software. We design the framework of the proposed BI system to predict customer churn in the telecommunication industry. The logic-based implementation and performance testing results of the constraint-based pattern mining are also illustrated in this paper.

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