First, sorry to have missed the gestalt references.

Second, I've now skimmed your manifesto.

I dunno that I can contribute anything of use to you since you picked Python and MySQL while I'm strictly Perl and PostgreSQL.

As for the "rebuild SAS" scenario, I'm not certain that SAS is the right approach to data analysis. The few places I've used/supported it, there were always a few FORTRAN guys on staff to handle tricky stuff that could not be done with SAS. I also remember that there was always a go-to guy to do data cleanup. Heck, when I was working at a DHHS agency, I developed several tools (under scientist supervision) with TurboPascal to avoid enormous CPU-usage costs at the NIH datacenter.

I know that SAS is the Cadillac standard, but it might make sense for you to pull-together the Python and MySQL tools and perform data analysis "by-hand" to for some of your work just to see if it can be done. If you tWikify all your steps and code, you may find what steps are worth "automating" and maybe get some review of your methods at the same time.

Again, my take would be to consider how much time you could afford in lieu of paying an annual recurring $6k.