slightly OT: data modelling question

Hi,
I am designing a (data warehouse) system where I would like to get some hints for the table design.
I have dimensions time, standard_width, category and dimension hierarchy
hierarchy has 5 levels with each having about 30 attributes level1 .. level5 identified by ids that are generated by production system per day via sequence - (8-10 attributes would make up the key, further systems to add data reference the ids),
between level n and level (n+1) is a n:m-relationship

Then I have
facts type 1 just related hierarchy level5 and time, standard_width, category
facts type 2 related to time and hierachy - hierarchy dimension is non-additive
facts type 3 related to time and hierachy,standard_width, category all facts are additive

Now I am wondering, do I construnct dimension hierarchy as a large dimension
(adding about 2000 records per day).

Or to I normalize the dimension having a table per level? If second solution how do I make sure performance for my facts of type 1 is still acceptable?

The system is to use one of this featureful adhoc-query-tools. Any tips?

Regards,
Antje Sackwitz

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