Data Warehouse is designed based on Schema's. Whenever we load the data into the warehouse it should be in the form of schema's. In the simple words, schema is nothing but structure of the data.
This structure of data is built mainly on two components called as "Facts and Dimensions". Based on this the complete data is divided into two parts as "Facts and Dimensions"
This schema's are categorized into 3 different types based on their characteristics and they are
Star Schema : It's called as "Star Schema" because its structure is similar to a star. It consists of both dimensions and facts tables in it. One fact table at the center and surrounded by denormalized (Duplicate) dimension tables. It can have more than one fact table.
Snow Flake Schema : It is an extension of the star schema. Here it adds additional dimension tables. So here there are many dimension tables which are normalized, as a result less duplicate data is stored than star schema. Snow Flake effects only dimension table but not Fact tables.
Galaxy Schema : It has many fact tables and surrounded with dimension tables. Here Fact tables contains many common dimensional tables.
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