Exploring and analyzing detailed business transactions. It implies "digging through tons of data" to uncover patterns and relationships contained within the business activity and history. Data mining can be done manually by slicing and dicing the data until a pattern becomes obvious. Or, it can be done with programs that analyze the data automatically. Data mining has become an important part of customer relationship management (CRM). In order to better understand customer behavior and preferences, businesses use data mining to wade through the huge amounts of information gathered via the Web. See data miner, Web mining, text mining, OLAP, DSS, EIS, data warehouse and slice and dice.
The goal of this credit card analysis is to determine the most influential factors common to non-profitable customers. In this case, BusinessMiner from Business Objects determined that the credit limit had the greatest effect on profitability and prioritized the results in graphical form. (Screen shot courtesy of Business Objects.)
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