Definition: Analysis of a number of datasets
in search of patterns.
Explanation: You can use a collection of
datasets and by looking at them all for a particular item or items you can
possibly discover information that would not be available by looking at any of
the datasets singly. The datasets do not
have to be identical in structure. It is
possible to use data mining in an exploratory manner.
Example: An early use mining data in search
of patterns came from the desire to analyze supermarket transaction data, that
is, to examine customer behavior in terms of the purchased products. For example, an association rule "beer
=> crisps (80%)" states that four out of five customers that bought
beer also bought crisps. (Source: Wikipedia.org, http://en.wikipedia.org/wiki/Data_mining )
Why it is important:
It enables us to turn
data into information.
Contributed by BES Information Manager Jonathan Walsh
