This is important: Any insights drawn from big data that show emergent trends, can ONLY be applied statistically to large collections of data.
Trying to apply big data findings to an individual case in order to determine outcome will usually fail.
For example, big data mining may reveal that there is a positive correlation between claim length (word count) and claim scope.
You could then apply this finding to a whole portfolio and say, these 1000 patents are likely narrower in scope to these 1000 patents.
But pick up one patent and try to make a determination on claim length and scope, and likely you will fail to get it right. On the individual level there are just too many variables.
This must have an analog in economic theory?