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There is a dataset which contains aggregated data - aggregated to various dimensions, and down to the hourly level. The main measure is speed which is simply the file size divided by the duration.

The requirement is to see Percentile, Median and Average/Mean summaries.

Mean is simple because we simply create a calculated measure in the MDX and then it works at all aggregation levels i.e. daily/monthly etc.

However Percentile and median are hard. Is there any way in which it is possible to have a calculation for these functions which will roll up correctly? We could add the percentile speed as a column in the ETL when we're reading the raw data, but we'd still need to find a way to then roll it up further?

What is the proper way to roll up these types of measures? It's not uncommon to ask for percentile numbers, so I'm surprised to not see much information on this when I look around.

Maybe the only approach is to have various aggregated tables at the right level, with the right calculation, and then make mondrian use them as agg tables? Or worse case have multiple cubes (!)

Codek
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OK, so it turns out you cannot roll up percentiles ( and therefore medians which is just a 50th Percentile ) I understand others have had this problem, see this tweet from Kasper here: https://twitter.com/kaspersor/status/308189242788560896

So our solution was a couple of different agg tables to store the relevant stats, and on the main (already aggregated) fact table to store the pre-computed percentile and median stats.

Codek
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