Snowflake Schema is describes a logical database structure of Data Warehouse or Data Mart. Snowflake Schema can design with one de-normalized FACT and one or many normalized Dimension table(s). Snowflake Schema is an extended and normalized STAR Schema.
The following STAR Schema is describes a Sales Data Mart that designed with de-normalized Sales_Fact and relevant shared dimension tables to maintain Sales Historical Transaction information.
Snowflake Schema often uses in Data Warehouse that helps to optimize database query operation. First Normal Form, Second Normal Form and Third Normal Form rules must apply on Dimension in the Snowflake Schema. Grain is the base business definition of Fact table that determine measurement of business event.
Normalization Technique is used to eliminate data anomalies, minimize data redundancy, minimize data storage memory, improve data integrity and simplify the database query process in the Relational Database Model.
The following Snowflake Schema is describes a Sales Data Mart that designed with de-normalized Sales_Fact and relevant normalized dimension tables to maintain Sales Historical Transaction information.