Database Reference
In-Depth Information
grain but rather at the State grain. We'd have a source table with columns such as
follows:
•
ProjectionDate
•
StateID
•
ProjectedGrowth
We can't join this new source table to our existing Geography dimension because if
we do so, we will get back many surrogate keys—each representing one postal code
within the specified state. So, we need to Snowflake (partially normalize) the Geo-
graphy dimension so that it will support the grain of each of our fact source tables,
giving us two dimension tables similar to the the following two bullet lists:
dimGeography
:
•
skGeography
•
PostalCode
•
CityID
•
CityName
•
skGeographyState
and
dimGeographyState
:
•
skGeographyState
•
StateID
•
StateName
•
CountryID
•
CountryName
Notice that we did not fully normalize the dimension (postal code and city both exist
in the first table, state and country in the second). We just normalized the dimension
enough to give us a single relationship between each of our two facts and this di-
mension.
Search WWH ::
Custom Search