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I am setting up a work computer and have free reign here. My typical go-to software packages are all freely available, such as Rstudio and Anaconda.
I have thought about investing in commercial BI software such as Tableau or Spotfire, but nobody else in the group (or myself) is a proficient user. Are there other obvious choices I am missing?
At the outset, much of what this group is working on will be exploratory. They are needing some justification to invest further into "data science".
If you are a data scientist, then there is very little use for pre-packaged, generally inflexible commercial tools.
Part of the reason OSS is so prevalent and useful in data science is that you will often need to combine and/or modify a procedure to fit the needs at hand -- and then deploy it without a bunch of lawyers and sales reps getting involved at every step.
Since data scientists are expected to be proficient programmers, you should be comfortable digging into the source code and adding functionality or making it more user friendly.
I've come close to recommending the purchase of non-free(as in GPL) a couple times only to find that some industrious person has set up a project in Git that provides most if not all of the functionality if commercial software. In the cases where it doesn't, it at least addresses the core issue and I can modify and extend from it. It's much easier to modify a prototype than start from scratch.
Bottom line: be wary of commercial software for data science unless you've done your due diligence in the OSS space and can honestly say that you could not find any projects that could be modified to suit your needs. Commercial software is not only less flexible but you're effectively in a business partnership with these folks and that means your fates are somewhat intertwined (at least for the projects that depend in this software).
If you are looking for a technical package I would definitely go with Mathematica. It has functions for a very wide range of disciplines that come standard with it (no extra packages to buy). This allows you to expand into techniques as you grow without having to change platforms or buy extra packages. It also has a great interactive format in CDF with both a free and professional reader. The documentation is interactive as well which really helps a lot.
However, you have to be open to a little bit of structure, typing & chaining functions together, and things like this. Once you get started it comes very quickly.
I would echo @David. The question is what do you expect the tool to serve. May be SAS or SPSS is the way to go or even MATLAB. Each tool brings something to the table. Depending on what you need, one or more may fit the bill. Also look at your org's tech road map. If Open Source is a big push, your list may be different.
Tableau is a good tool (and easy to learn) for Business Users or people who are less technical. Even though it is costly ($2000 for a single user annual license), it has a good reader (free) and once a report is generated, the users can leverage the reader and update without dependence on the license holder. The benefit will lie as long as the reports are stable and standard in nature.
R has great graphic capabilities and hence users who do get involved in analytic may find it better suited. Similarly python can be a great tool especially if you need a web based solution for your users.
So think about your needs and strategy.
