One of the most interesting and valuable dimensions in a 
data warehouse is one that explains why a fact table record 
exists. In most data warehouses, you build a fact table 
record when something happens. For example: 

When the cash register rings in a retail store, a fact 
table record is created for each line item on the sales 
ticket. The obvious dimensions of this fact table record 
are product, store, customer, sales ticket, and time. 
At a bank ATM, a fact table record is created for every 
customer transaction. The dimensions of this fact table 
record are financial service, ATM location, customer, 
transaction type, and time. 
When the telephone rings, the phone company creates a fact 
table record for each "hook event." A complete call-
tracking data warehouse in a telephone company records each 
completed call, busy signal, wrong number, and partially 
dialed call. 
In all three of these cases, a physical event takes place, 
and the data warehouse responds by storing a fact table 
record. However, the physical events and the corresponding 
fact table records are more interesting than simply storing 
a small piece of rev enue. Each event represents a 
conscious decision by the customer to use the product or 
the service. A good marketing person is fascinated by these 
events. Why did the customer choose to buy the product or 
use the service at that exact moment? If we only had a 
dimension called "Why Did The Customer Buy My Product Just 
Now?" our data warehouses could answer almost any marketing 
question. We call a dimension like this a "causal" 
dimension, because it explains what caused the event.