Understanding the different types of schemas (snowflake and star)
When you create a data model, the arrangement of the dimension and fact tables can help you understand how the data flows from the dimension tables to filter the fact tables containing our key measures.
At the heart of our analysis are the key measures we will calculate from our fact tables. These fact tables are normally placed at the lower section of the data model, and our dimension tables are placed on top.
In certain layouts, you can also place the fact tables in the middle surrounded by dimension tables. This type of layout where several dimension tables are connected to one or multiple fact tables placed below or at the center of the dimension tables is called a star schema.
Figure 4.17 – Star schema in a data model
This is a common layout or schema for most data models. It ensures that your calculations are well optimized because it has only dimension tables of one level...