That would work very well if our random sample accurately reflected the superset of data,which it almost always does but you also want to consider the following...
Imagine our data was 98% junk with 2% of the data consisting of sequential patterns. We may be able to spot this on a graph relatively easily over the whole dataset but our random sampling would greatly reduce the quality of this information.
We can extend that to any ordering or periodicity in the data.if data at position n has a hidden dependency of data at position n+/-1 random sampling will break us.
Imagine our data was 98% junk with 2% of the data consisting of sequential patterns. We may be able to spot this on a graph relatively easily over the whole dataset but our random sampling would greatly reduce the quality of this information.
We can extend that to any ordering or periodicity in the data.if data at position n has a hidden dependency of data at position n+/-1 random sampling will break us.