When you look at the STAR schema, you find that it is simply a relational model with a one-to-many relationship between each dimension table and the fact table. What is so special about the arrangement of the STAR schema? Why is it declared to be eminently suitable for the data warehouse? What are the reasons for its wide use and success in providing optimization for processing queries?
Although the STAR schema is a relational model, it is not a normalized model. The dimension tables are purposely denormalized. This is a basic difference between the STAR schema and relational schemas for OLTP systems.
Before we discuss some very significant advantages of the STAR schema, we need to be aware that strict adherence to this arrangement is not always the best option. For example, if customer is one of the dimensions and if the enterprise has a very large number of customers, a denormalized customer dimension table is not desirable. A large dimension table may increase the size of the fact table correspondingly.
However, the advantages far outweigh any shortcomings. So, let us go over the advantages of the STAR schema.
Users of OLTP systems interact with the applications through predefined GUI screens or preset query templates. There is practically no need for the users to understand the data structures behind the scenes. The data structures and the database schema remain in the realm of IT professionals.