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Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. [ 2 ] The star schema gets its name from the physical model's [ 3 ] resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points.
Example of a star schema; the central table is the fact table. In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation ...
The cube metadata is typically created from a star schema or snowflake schema or fact constellation of tables in a relational database. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables. Each measure can be thought of as having a set of labels, or meta-data associated with it.
These schemas are implemented for complex data warehouses. [1] The fact constellation is a measure of online analytical processing and can be seen as an extension of the star schema. A fact constellation schema has multiple fact tables. It is a widely used schema and more complex than star schemas and snowflake schemas.
The dimensional model is built on a star-like schema or snowflake schema, with dimensions surrounding the fact table. [3] [4] To build the schema, the following design model is used: Choose the business process; Declare the grain; Identify the dimensions; Identify the fact; Choose the business process
The reverse star schema is a schema optimized for fast retrieval of large quantities of descriptive data. The design was derived from a warehouse star schema , [ 1 ] and its adaptation for descriptive data required that certain key characteristics of the classic star schema be "reversed".
Star schemas, which are also known as fact-dimension models and have been extended to snowflake schemas Prebuilt summarization or OLAP cubes With the continued dramatic increase in all three of storage, processing power and bandwidth, on all levels, denormalization in databases has moved from being an unusual or extension technique, to the ...