Scope: A billion record table that is indexed in 10 ways. Rate of change per day is 1/2 a percent.

Some of the indexes are monotonously increasing (datetime/timestamp), yet the common queries most likely hit the tail end. I assume statistics need updating frequently for this type, otherwise the recent data becomes unrepresented in the index?

Other indexes are more randomly distributed, e.g. (Customer Key, Datetime). These can do with less frequent updates, since the statistics are quite representative of the whole. We can let the index change enough to force auto statistics updates on these, correct?

For both types, is there any benefit from increasing the sampling from 10% to 100%, if the data to be sampled is random and quite representative of the whole?

Looking for best practice with TB data.