This is true of any dimension that can be used across multiple data marts. Time,
product, employee, and customer are just a few examples of dimensions that commonly
are used across multiple data marts. Whether these tables are actually only stored once
and linked to different fact tables, or whether they are physically stored multiple times,
their structure should be the same. Using conformed dimensions prevent what are
sometimes called ???stovepipe data marts,??? or marts that stand alone in their own silo and
cannot be integrated with other data marts.
Slowly Changing Dimensions One of the biggest issues you??™ll encounter when dealing
with dimensions is how to handle changes. Change is inevitable and here are two
examples of this:
A company tracks salespeople and the manager to which they report. Each
salesperson is rewarded based on his or her sales, and each manager is
rewarded based on the performance of the salespeople he or she manages. After
a district realignment, some salespeople move from one manager to another.
The salespeople need their history to go with them, but sales made under their
previous manager should still be in that previous manager??™s numbers.
A company wants to increase the profi t on an item without increasing the
price, so they decide to drop the item??™s size from 16 ounces to 14 ounces while
maintaining the same price. Simply updating the fi eld in the database from 16
to 14 makes it look like the product has always been 14 ounces and thus history
is lost as to when the change occurred.
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