What matters in terms of better value is whether or not one can understand the problems space and find an appropriate solution for it. All sorts of solution space solutions can be used, some of which are better than others. The point is to try and keep it simple enough for the user, irrespective of how difficult it might be for the IT guy.
The knowledge of Hadoop in and of itself is not as valuable as one would suggest it is.
[Edit fix wording]
Hiring a hadoop guy for what used to work in excel is a bad decision in most ceases...
as opposed to fecking sharepoint
Yes but https://aadrake.com/command-line-tools-can-be-235x-faster-th...
"Since the problem is basically just to look at the result lines of each file and aggregate the different results" which is why this works on this data for this problem. Many problems are not efficient to solve in this way, for example searches through large products and expansions, especially where the evaluation function is costly.
Some problems are data bound - you are handling 100'sTb of data, hadoop can be a good fit.
Some problems are CPU bound, and embarrassingly parallel - you require massive parallelism to get through the core seconds that you need to solve the problem. If you need 1 million core seconds and you have 1000 cores, and a way of getting the 1000 cores to do 1/1000th of the work... all is good.
Some problems are memory bound. You can build single space machines with many TB memory now, also you can cache with SSD's and optanes more than in the past, but Hadoop does offer a utility for these problems.
But in a corporate all problems are admin and discovery bound. If your dataset is what I need and I don't know about it, can't find it and anyway if I did then you won't give it to me and I can't unlock it legitimately; I am screwed. If it's a proper corporate asset then I've got a fighting chance.
End users groan because people groan every time anything changes and they have to learn something new.
https://support.office.com/en-us/article/Connect-to-a-Hadoop...