IMHO, I've never been a "fan" of transforming data, because interpreting the results is always problematic (telling a client about the log of the data points will always get you a puzzled look --> not good).
If the data are skewed badly enough, then you may want to consider:
(1) finding probable causes for the "outliers" and removing them, or
(2) using a nonparametric method
However, if there's a really, really good reason, then there are virtually unlimited ways to transform data - just make sure you pick the one that meets your analytical needs....