Adding additional dimension tables to a Star Schema makes it a
Snowflake Schema. In the Snowflake schema model, multiple hierarchies of dimension tables surround a central fact table. Alternatively, a dimension table is called a snowflake if its low-cardinality attribute has been segmented into separate normalized tables. These normalized tables are then joined with referential constraints (foreign key constraints) to the original dimensions table. Snowflake schema complexity increases linearly with the level of hierarchy in the dimension tables.
Advantages :
* Data integrity is reduced because of structured data.
* Data are highly structured, so it requires little disk space.
* Updating or maintaining Snowflaking tables is easy.
Disadvantages :
* Snowflake reduces the space consumed by dimension tables, but the space saved is usually insignificant compared with the entire data warehouse.
* Due to the number of tables added, you may need complex joins to perform a query, which will reduce query performance.
