I have a fact that has around 1K different numerical attributes (i.e. columns). I would like to store this in to a column-oriented DB and perform cube analysis on it.
I tried to design a star schema, but I'm not sure how to handle this many columns. Normalising it sounds wrong, but I can't just have flat columns either. The combination of attributes are also too diverse to have a simple dimension table for this, even if I'd reduce the numerical values into categories (ranges), which is an option. I thought about storing them as XML or JSON for each row, but that doesn't sound great either.
If it helps, I'm planning to use Amazon's redshift for the DB.
Note: We have strong preference for RedShift as it fits perfectly for at least other few operations we do on this data. Hence I want to avoid other technologies like HBase if possible.