The ability to store on-line large quantities of information makes possible new forms of analysis. A data warehouse typically consists of a database containing large quantities of business information that can then be mined for new forms of information.

Consider, for example, the current practice by local supermarkets to offer customers a special discount shopping card:

1. The card identifies you to the supermarket, even if you are paying in cash. Your name can be matched to credit and demographic information from reporting agencies.
2. Check-out scanners uniquely identify every item that you purchased and the date/time of the transaction.

This all becomes a giant warehouse of data on customer purchases that managers can mine for shopping trends. Sophsticated analysis tools enable management to predict consumer trends, plan targeted promotions, and even offer specials based on personal buying history.

Data mining is not limited to commercial transactions. The City of New York Police Department established a geographic database of all crimes and arrests throughout the city. It now mines this data to identify new crime trends and to allocate police resources for maximum effectiveness. News resports claim that this data mining has played a critical role in both decreasing the crime rate and increasing the percentage of successful arrests.

Data mining has local implications for both:

Academic	How do we prepare our business students to become proficient in the use of mining tools and the effective interpretation of the findings?
Administrative	How does the College mine its available information to forecast enrollment trends and maximize operational efficiency?