[erikb]

I think you can have both situations. I still remember a talk from a Google person maybe around 2010 where he showed clearly that if you try to make the data "better" but in general have way too little data points, then it can't be useful either.

It's just now that we had almost a decade of pushing towards more IoT and more Big Data, that many companies have huge data lakes that they don't know how to make use off.

So instead of applying one of these lessons it's probably best to see where one is lacking (quantity or quality) and work on resolving that specific problem accordingly.