I'm a hard science/computer science guy who's livelihood is working on various NIH/NSF projects. A common thread talking to other scientists the past few years has been the theme that the tools for data analysis have not kept pace with the tools for data acquisition. Companies like National Instruments sell sub-$1000 USB DAQ boards with resolution and bandwidth that would make a scientist from the early 1990's weep for joy. But most data analysis is done the same way it's been done since that same era: with a desktop application working with discrete files, and maybe some ad-hoc scripts. (Only now the scripts are Python instead of C...)
The funny thing is, most researchers haven't yet wrapped their brains around the notion of offloading data onto cloud computing solutions like Amazon AWS. I was at an AWS presentation a couple months ago, and the university's office of research gave an intro talking about their new supercomputer that has 2000 cores, only to get upstaged 10 minutes later when the Amazon guys introduced their 17000 core virtual supercomputer (#42 on the top 500 list, IIRC). There's a lot of untapped potential right now for using that infrastructure to crunch big data.
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