Star Schema
Star Schema
A star schema is a type of data warehouse that arranges data in a central fact table surrounded by multiple dimension tables. This structure simplifies complex data queries and provides efficient access to data from different perspectives.
What does Star Schema mean?
A star schema is a data warehouse Design Pattern that is used to store and access multidimensional data. It consists of a central fact table that contains the numeric data, and a number of dimension tables that contain the descriptive data. The fact table is linked to the dimension tables by foreign keys.
Star schemas are designed to be efficient for data warehousing because they allow for quick and easy access to data. This is important because data warehouses are often used to support decision-making and Analysis, which require fast and efficient access to data.
Star schemas are also relatively easy to understand and maintain, which makes them a popular choice for data warehouses.
Applications
Star schemas are used in a variety of applications, including:
- Data warehousing: Star schemas are the most common data warehouse design pattern. They are used to store and access multidimensional data for decision-making and analysis.
- Business intelligence: Star schemas are used to create business intelligence reports and dashboards. These reports and dashboards can be used to track Key Performance Indicators (KPIs) and make informed decisions.
- Data mining: Star schemas are used to mine data for patterns and trends. This information can be used to improve business processes and make better decisions.
History
The star schema was first developed in the early 1990s by Ralph Kimball. Kimball was a data warehouse architect who was looking for a way to design data warehouses that were efficient and easy to use.
Kimball’s star schema design has become the most popular data warehouse design pattern. It is used by a wide variety of organizations, including Fortune 500 companies and Government agencies.