I don't think we should necessarily aim to make "serious tools" easy for people to get into. I am not saying that the UI shouldn't be intuitive, but rather that making something 'too easy' results in low barriers to entry and you end up with the wrong types of people using that tool. Excel is very useful (I use it much in the same way the OP does), but it has it's limitations. Because it is so easy to get into, it's easy for individuals lacking the proper experience to over extend themselves.

I think much of the explosion in data science jobs these last few years isn't really about "big data", but rather the fact that your typical corporate analyst does not have the experience to tackle mid range data analysis jobs because the only tool they have under their belts is Excel. What really is needed is a larger number of people with experience in statistics, scientific computing (Python, R etc..), and database systems. The current tools we have are fine, they just need to be used properly (well, we should always strive to improve our tools, but you get the idea).