There are a lot of good suggestions in this discussion so far.
I have a few points to add.
1) compiled language vs scripting language
In general, any compiled language is going to run faster than any scripting language. But you will probably spend more time coding and debugging to get your analysis running with a compiled language. It is useful to think about how important performance is to you relative to the value of your own time. Are you going to be doing these data mining runs repeatedly? Is it worth spending ten times as many hours getting this thing up and running if by doing so, you can get it to run really fast? If so, than chose a compiled language. You're already familiar with C so that would be a natural choice. If, after consideration, you value your development time more than processing time, stick with a scripting language. You'll probably be able to stand up a working program much faster & you can look for other ways to squeeze out extra performance
2) Parallelism. Your initial question explicitly said you want to use all 4 cores on a Xeon, but I've only seen 1 response so far that addresses this issue. To get good performance out of multiple cores you may need to re-work your algorithms to split the problem into pieces and crunch them down in parallel. Is your problem one that is easily amenable to parallelization? If yes, then you probably want to start thinking about multi-thread or multi-process programming. If your program will never run on something bigger than 1 server, than you will probably be OK sticking with with single multi-threaded process. I don't have experience in this myself, but I've heard that writing your program in a functional language like Haskell will make it intrinsically easy to parallelize. If you ever think your program is going to run on something bigger than that Xeon server - let's say you're thinking of ramping up to a cluster, than I would suggest building it on top of MPI from the beginning. I've had good results getting something up and running on MPI quickly using a combination of python, NumPy, SciPy and mpi4py.