What are factless fact tables in data warehousing?

Data warehousing combines information and data from different sources into a single, complete database.

Factless fact tables

The fact tables with no measurements linked with the transaction are known as factless fact tables. They are a straightforward grouping of dimensional keys that identifies transactions.

Importance

Factless fact tables are very useful. They are significant dimensional data structures that collect crucial information that can be used in rollup measures or as information displayed to a user.

Examples

Some common examples of factless fact tables are as follows:

• Ex-office visitors

• Tracking student attendance events

• Tracking student registration events

• List of individuals for site clicks

Types of factless fact tables

There are two types of factless fact tables as follows:

• Event tracking tables

• Coverage tables

Event tracking tables

To keep track of events that are important to an organization, we use a type of factless fact table called an event tracking table. For example, it could be used to tally attendance at a cultural event.

Coverage tables

This is the second type of factless fact table. A coverage table is used to do a negative analysis of given reports. For example, if a product has not sold for a certain period of time at a store, we can create a coverage table that will contain all possible combinations of reasons as to its low selling rate.