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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]
In computing, the star schema or star model is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. [1] The star schema consists of one or more fact tables referencing any number of dimension tables .
[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 process of dimensional modeling builds on a 4-step design method that helps to ensure the usability of the dimensional model and the use of the data warehouse.
A fact constellation schema, also referred to as a galaxy schema, is a model using multiple fact tables and multiple dimension tables. [1] 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.
The dimensional model is a specialized adaptation of the relational model used to represent data in data warehouses in a way that data can be easily summarized using online analytical processing, or OLAP queries. In the dimensional model, a database schema consists of a single large table of facts that are described using dimensions and measures.
Besides these basic elements, the DFM includes a large set of constructs for expressing the multitude of conceptual nuances that characterize actual modeling scenarios in projects of small to large complexity. A multidimensional schema modeled with the DFM can easily (i.e., semi-automatically) be implemented on both ROLAP and MOLAP platforms.
In the field of database design, a multi-model database is a database management system designed to support multiple data models against a single, integrated backend. In contrast, most database management systems are organized around a single data model that determines how data can be organized, stored, and manipulated. [ 1 ]
The notion of a three-schema model was first introduced in 1975 by the ANSI/X3/SPARC three level architecture, which determined three levels to model data. [1]The three-schema approach, or three-schema concept, in software engineering is an approach to building information systems and systems information management that originated in the 1970s.