Interesting Example of Data Mining: Beer and Diapers

Some time ago, Wal-Mart decided to combine the data from its loyalty card system with that from its point of sale systems. The former provided Wal-Mart with demographic data about its customers, the latter told it where, when and what those customers bought. Once combined, the data was mined extensively and many correlations appeared. Some of these were obvious; people who buy gin are also likely to buy tonic. They often also buy lemons. However, one correlation stood out like a sore thumb because it was so unexpected.

On Friday afternoons, young American males who buy diapers (nappies) also have a predisposition to buy beer. No one had predicted that result, so no one would ever have even asked the question in the first place. Hence, this is an excellent example of the difference between data mining and querying.