When a fact table does not contain any facts, it is called afactless fact table. There are two types of factless fact tables: those that describe events, and those that describe conditions. Both may play important roles in your dimensional models.
Factless fact tables for events
Sometimes there seem to be no facts associated with an important business process. Events or activities occur that you wish to track, but you find no measurements. In situations like this, build a standard transaction-grained fact table that contains no facts.
For example, you may be tracking contact events with customers. How often and why we have contact with each customer may be an important factor in focusing retention efforts, targeting marketing campaigns, and so forth.
The factless fact table shown here captures a row each time contact with a customer occurs. Dimensions represent the date and time of each contact, the customer contacted, and the type of communication (e.g. inbound phone call, outbound phone call, robo-call, email campaign, etc.).
While there are no facts, this kind of star schema is indeed measuring something: the occurrence of events. In this case, the event is a contact. Since the events correspond to the grain of the fact table, a fact is not required;
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