Categorisation and Classification

Perhaps the most common datamining task is categorisation.
Data items are defined by a vector of fields. One of the fields is the category.
Your system learns from the data items to categorise new items.
Classification is similar but the data items don't contain the category.
I'm not a big datamining guy, but a standard machine learning research paradigm is to use a standard benchmark.
A really commonly used one (the most commonly used one) is University of California at Irvine's Categorisation Benchmark
Its used to compare algorithms.
Its also not a bad way to exercise your datamining skills.
Note that no algorithm is better than all others on all data sets; there's no free lunch.