  Business intelligence (BI) is any knowledge derived from existing data that
may be strategically applied within a business. Data mining is a technique or
method for extracting BI from data using statistical data modeling. Finding
relationships or correlations between the various data items that have been
collected can be used to boost business performance or at the very least better
comprehend what is going on. Root cause analysis (RCA) is discovering the root
causes of problems or events to identify appropriate solutions. RCA can show
why an event occurred and this can help in avoiding occurrences of an issue in
the future. This paper proposes a new clustering + association rule mining
pipeline for getting business insights from data. The results of this pipeline
are in the form of association rules having consequents, antecedents, and
various metrics to evaluate these rules. The results of this pipeline can help
in anchoring important business decisions and can also be used by data
scientists for updating existing models or while developing new ones. The
occurrence of any event is explained by its antecedents in the generated rules.
Hence this output can also help in data-driven root cause analysis.
