I hated SAS for years. Because I believe the language is plain ugly, overcomplicated and unintuitive. The main pain: the fact that any DATA or PROC step (what's the difference anyway?) has a closed structure. Also, it's slow. For trial and error programming, SAS is to avoid. I still believe that.
But, sometimes, you just lack the RAM to work in beautiful languages like Stata or R. So you need to use the statistical WMD. To speed up work, there's this golden tip: compress the data sets (compress=binary). More on this here:
http://heuristically.wordpress.com/2010/08/13/make-sas-faster-data-set-compression/
