> You probably just need better buzzwords (and ideally the background to back it up) -- NoSQL, big data, MongoDB, Hadoop, etc.
Are there as many data scientists who don't work on Big Data?
Are there as many data scientists who don't work on Big Data?
There are plenty of data problems out there already warehoused by small-cap and mid-cap firms; I honestly don't see a need to go Web-Scale and all that jazz for its own sake if your use case doesn't need it. There's also shortcuts like sampling to kick the can down the road, but that's another discussion in and of itself.
Or, I guess programmers and engineers could start using the big data tools even though they are not needed. Has anyone ran Hadoop on a single (multi-core) machine for this purpose?
Check out http://www.kdnuggets.com/ for links to large data sets to work on and there are also some on amazon.
Also, yes you can certainly run hadoop on a single instance, but once you get into "real big" sizes you'll need a cluster to demonstrate expertise, be it on your local machines at your house or on a set of VPS or EC2 or whatever.
As a math/stats guy who picked up more programming along the way, I personally think it's MUCH easier to train a DB guy some business sense than it is for a a business analyst to have Hadoop drilled into them. Of course, the downsides of a coder without sufficient savvy are harder to detect than a numbers guy who can't make his program work, and therein lies your problem.