A star schema is used as a basic implementation of an OLAP cube. If your fact table contains a 1 to many relationship to each of your dimensions in your data warehouse schema then it is appropriate to use a star schema. Although if your fact table has a many to many relationship with its dimensions (i.e. many rows in your fact equal many rows in your dimension) then you must resolve this using a snow flake schema where the bridge table contains a unique key to each row in the fact table.
An example of a 1 to many relationship (star schema) is a fact table which contains sales data, and a dimension table which contains a list of stores. 1 store can have many sales but each sale only comes from 1 store. i.e. 1 row in the dimension table can equal many rows in the fact table.
To modify the above example to make it a snow flake schema would be as follows:
a store can have many sales but each sale can come from many stores. This would be a many to many relationship and you would need a bridge table to implement this functional requirement.
An example of a 1 to many relationship (star schema) is a fact table which contains sales data, and a dimension table which contains a list of stores. 1 store can have many sales but each sale only comes from 1 store. i.e. 1 row in the dimension table can equal many rows in the fact table.
To modify the above example to make it a snow flake schema would be as follows:
a store can have many sales but each sale can come from many stores. This would be a many to many relationship and you would need a bridge table to implement this functional requirement.
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