Types of fact tables
Upon close examination, the business events that we want to observe have different temporal properties. They may be occasional, recurrent or even change over time. Let’s discover the different types of fact tables that can be used to model them.
Factless fact table
How can we model a business process for which the only useful information concerns whether or not an event has taken place? And how should we proceed if no events can even be associated with this business process? Let’s discover the factless fact table.
Bridge table
We sometimes find that certain situations cannot be modeled by a snowflake schema. We then need to add a table known as a bridge table between two dimensions, or between the fact table and a dimension, which will enable us to resolve some of the problems described in this section.
Slowly changing dimension
Data dimensions enable us to analyze and observe measures according to different properties. How should we proceed when elements in this catalog change slowly over time?
Mini-dimension
In certain situations, dimensions are sufficiently massive or change much too quickly to enable the application of the solutions used for slow changes, which would create excessively large dimension tables. Mini-dimensions can resolve this problem.
Outrigger dimension
Creating a star schema does not necessarily require all dimensions to be linked to the fact table. There are certain specific situations in which a link can be established between two dimensions.
Annotations of dimensional schemas
Once you have learned all the main concepts, you should learn the annotations that will enable you to improve the documentation of your dimensional schemas.