Data Warehousing - Snowflake Schema
Understanding the Snowflake Schema
The snowflake schema is a schema design used in data warehousing that normalizes dimension tables to reduce redundancy.
Key Points:
- The snowflake schema is an extension of the star schema.
- Dimension tables in a snowflake schema are normalized into multiple related tables.
- Normalization reduces storage space and improves data integrity.
Components of a Snowflake Schema
Fact Table: Contains numerical data and foreign keys to dimension tables.
Dimension Tables: Normalized tables containing descriptive attributes related to dimensions (e.g., time, geography, product).
Advantages of Snowflake Schema
Reduced Redundancy: Normalization reduces data redundancy.
Data Integrity: Improves data integrity through normalized tables.
Scalability: Easier to scale with additional dimensions.
Use Cases
Snowflake schemas are suitable for complex data models requiring high data integrity and where storage efficiency is critical.
Conclusion
Understanding the snowflake schema helps in designing efficient data models that prioritize data integrity and storage efficiency in data warehousing.