

What is a Star Schema?
How does a Star Schema work?
Numeric numbers and dimension attribute values are both stored in the fact table. As an example, consider the following:
Numeric value fields are unique to each row or data point, and they have no correlation or relationship to data in other rows. These might include transactional details like the order ID, total money, net profit, order quantity, or precise time.
The foreign key value for a row in a linked dimensional table is stored in the dimension attribute values, rather than data. This sort of information will be referenced in several rows of the fact table. It could hold the sales staff ID, a date value, a product ID, or a branch office ID, for example.
The fact table’s supporting information is stored in dimension tables. Every Star Schema database has at least one dimension table. Each dimension table will be linked to a dimension value column in the fact table and will hold extra information about that value.
An example of a Star Schema
The employee dimension table may contain information such as the employee’s name, gender, address, or phone number, and may use the employee ID as a key value.
A product dimension table can hold data such as the product name, manufacturing cost, color, and first-to-market date.

Characteristics of Star Schema
Because of the following characteristics, the Star Schema is ideally suited for data warehouse database design:
- It builds a denormalized database that responds to queries rapidly.
- It has a flexible architecture that can be readily updated or added to as the database grows and the development cycle progresses.
- It gives a design equivalent to how end-users normally think of and utilize the internet.
What is modern-day data virtualization? How Lyftrondata enables data virtualization on Snowflake? – Part I
Advantages of a Star Schema
Shortcomings of a Star Schema
- Inflexible and lacks data integrity in a highly denormalized Schema state.
- Many-to-many relationships aren't supported within business entities.
- One-off inserts and updates can result in data anomalies.
Top ETL tool for 2021- make the best choice to achieve a data-savvy enterprise
How Lyftrondata helps

