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Business intelligence (BI) is any knowledge derived from existing data thatmay be strategically applied within a business. Data mining is a technique ormethod for extracting BI from data using statistical data modeling. Findingrelationships or correlations between the various data items that have beencollected can be used to boost business performance or at the very least bettercomprehend what is going on. Root cause analysis (RCA) is discovering the rootcauses of problems or events to identify appropriate solutions. RCA can showwhy an event occurred and this can help in avoiding occurrences of an issue inthe future. This paper proposes a new clustering + association rule miningpipeline for getting business insights from data. The results of this pipelineare in the form of association rules having consequents, antecedents, andvarious metrics to evaluate these rules. The results of this pipeline can helpin anchoring important business decisions and can also be used by datascientists for updating existing models or while developing new ones. Theoccurrence of any event is explained by its antecedents in the generated rules.Hence this output can also help in data-driven root cause analysis.

A Pipeline for Business Intelligence and Data-Driven Root Cause Analysis on Categorical Data