Split Fact Tables by Subject Area or Granularity?

Hello

I am building a data warehouse that will store property lease data. The lease data can be grouped into lease expiries, lease renewals, and vacancy, each of which has several measures associated with them. All measures from all groups have the same level of granularity (they all link to the same dimensions at the same levels).

My question is whether it would be best to build fact tables for each grouping (i.e.: lease expiry measures go in one fact table, lease renewal measures go in another), or have a single lease fact table where all measures will be placed (seeing as they are at the same level of granularity). It could be the case that with the latter, certain measures may be NULL at times if no value is available.

I am also considering the implications of this in terms of cube design (i.e.: I might want to group measures by these groupings to make it easier for users to find related measures when doing analysis), but I imagine that selecting certain groups of measures from the single fact table when creating the data source views would facilitate this.

Thanks.