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The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]
A transactional table is the most basic and fundamental. The grain associated with a transactional fact table is usually specified as "one row per line in a transaction", e.g., every line on a receipt. Typically a transactional fact table holds data of the most detailed level, causing it to have a great number of dimensions associated with it.
Consider a database of sales, perhaps from a store chain, classified by date, store and product. The image of the schema to the right is a star schema version of the sample schema provided in the snowflake schema article. Fact_Sales is the fact table and there are three dimension tables Dim_Date, Dim_Store and Dim_Product.
Snowflake Inc. is an American cloud-based data storage company. Headquartered in Bozeman, Montana, it operates a platform that allows for data analysis and simultaneous access of data sets with minimal latency. [1] It operates on Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.
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The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
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