There is little space savings overall because, as previously
mentioned, dimension tables take up only a very small portion of the storage of a
warehouse. In addition, the building of the cubes, to be described later, is slightly
slower due to the need to perform joins. However, once the cube is built, there is no
performance penalty from creating a snowflake schema.
Conformed Dimensions A special consideration is that of conformed dimensions. Since
most companies start with data marts, they end up with a number of different structures
for those different marts. One key element in bringing various marts together into a
warehouse is to have the same dimension structure across those marts. The structure
of the employee dimension in an HR data mart should match the structure of the
employee dimension in the Sales data mart, for example. Therefore, it is important to
ProductKey Product Category Product Subcategory Product Group SKU
1 Hardware Peripherals Mice 759U
2 Hardware Peripherals Mice A12Z
3 Hardware Printers Inkjet CC84
Product Name Weight Color Reorder Level Dealer Price
FragBoy Gaming Mouse 6 Black 25 22.95
Zed Laser Mouse 8 Grey 50 11.25
Onega Color Inkjet 180 Grey 12 43.50
Table 3-1 Three Records in a Product Dimension Table Show the Denormalization
Common in a Warehouse.
C h a p t e r 3 : D a t a W a r e h o u s i n g a n d B u s i n e s s I n t e l l i g e n c e 37
design dimensions up front not just for the current data mart, but with an eye toward
handling an entire enterprise data warehouse.
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