Yes your company's data may fit in RAM. But does every intermediate data set also fit in RAM ? Because I've also worked at a bank and we had thousands of complex ETLs often needing tens to hundreds of intermediate sets along the way. There is no AWS server that can keep all of that inflight at one time.
And what about your Data Analysts/Scientists. Can all of their random data sets reside in RAM on the same server too ?
$100K has always been "cheap" for a "business computer" and today you can get more computer for that money than ever.
$100K of hardware (per year or so) is small-fry compared to almost every other R&D industry out there. Just compare with the cost of debuggers, oscilloscopes and EMC labs for electronic engineers.
Buy them a machine each at a cost of $40-60 billion ?
Or would it make more sense to buy one Spark cluster and then share the resources at a fraction of the cost.
Still expensive, but much less than 40 billion.
We have a Spark cluster which supports all of those users for $10-$20k a month.
There is a trend, when the application is inefficient, to spend huge amount of resources on scaling it instead of making the application more efficient.