Question

SQL is the way of searching data to find results out of a database. Research the difference between a production database and a data warehouse. You will find that the design is different due to the purpose of them. In a data warehouse scenario, there are two common designs called the "Star" and "Snowflake" schemas. Discuss what a "Star" and "Snowflake" schema design for a database is, what it is

used for and how the two are different. How would your SQL be different for those two types of schemas?

Answer 1

The Star schema centers around a single fact table with denormalized dimension tables for quick queries, while the Snowflake schema involves a complex, normalized structure of tables that saves storage but requires more complex queries.

Step-by-step explanation:

The Star schema and Snowflake schema are two database design structures used in a data warehouse. The Star schema consists of a central fact table surrounded by dimension tables, resembling a star's pattern. It is optimized for query performance and simple queries, as it requires fewer joins and is typically denormalized.

The Snowflake schema is more complex, where dimension tables are normalized into multiple related tables, forming a structure that resembles a snowflake. This schema is beneficial from a data storage perspective but may result in more complex queries due to additional joins.

SQL queries for a Star schema might involve simple joins between the fact table and the dimensions, whereas queries for a Snowflake schema might require multiple joins to traverse the normalized hierarchy. Your choice between using a Star or Snowflake schema depends on if your priority is fast read-oriented access (Star) or storage space and update-oriented design (Snowflake).