Star Schema

Star Schema - Specific organization of a database often used in data warehouses. In this organization, a centralized fact table (table with specific pieces of information of interest to the users of the warehouse) with a composite key (a unique identifier made up of several other identifiers) is joined to a number of single-level dimension tables, each with a single primary key (or unique identifiers).

[Category=Data Governance ]

Source: The Data Governance Institute, 26 December 2009 10:33:57, http://www.datagovernance.com/glossary-governance/

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Star Schema - A method of organizing information in a data warehouse that allows the business information to be viewed from many perspectives.

The star is a picture of the way the data is being stored. The basic factual information is in the middle of the star. The points of the star represent various perspectives from which the factual information can be viewed. 

[Category=Data Warehousing ]

Source: SDG Computing Inc., 12 May 2010 11:23:37, SDG Computing, now offline

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Star Schema - A star schema is a set of tables comprised of a single, central fact table surrounded by de-normalized dimensions. Each dimension is represented in a single table. Star schema implement dimensional data structures with de- normalized dimensions. Snowflake schema are an alternative to star schema. A relational database schema for representing multidimensional data. The data is stored in a central fact table, with one or more tables holding information on each dimension. Dimensions have levels, and all levels are usually shown as columns in each dimension table.

[Category=Information Management ]

Source: Information-Management.com, 12 July 2010 09:23:08, http://www.information-management.com/glossary/m.html

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Star Schema - A database design characterized by its simplicity, allowing users to navigate through the data easily, and its rapid response time. Unlike traditional relational schemas, normalization is not a goal of star schema design. Star schemas are usually divided into fact tables and dimensional tables, where the dimensional tables supply supporting information, such as the demographics of the buyers who made up the entries in the primary fact table.

[Category=Data Warehousing ]

Source: Sun.com, 11 August 2010 08:32:16, http://www.sun.com/third-party/dw/brochures/67198.Acrobat.pdf

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Star Schema - A common form of dimensional model. In a star schema, central fact table surrounded by de-normalized dimensions, each dimension is represented by a single dimension table. This database design characterized by its simplicity, allowing users to navigate through the data easily, and its rapid response time. Unlike traditional relational schemas, normalization is not a goal of star schema design. Snowflake schema are an alternative to star schema.

[Category=Data Warehousing ]

Source: Aexis Business Intelligence, 25 December 2010 09:59:25, http://www.aexis.eu/DataWarehouse-Glossary/

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Star Schema - With a star schema for multidimensional modeling, the fact table sits in the middle of the diagram and all the dimensions hang directly off of the fact table thus resembling a star. The data in the dimension tables is denormalized to allow all other tables to link directly to the fact table.

[Category=Business Intelligence ]

Source: Deanna Dicken, 09 November 2012 09:22:28, http://www.databasejournal.com/features/mssql/article.php/3919011/Business-Intelligence-Terminology-101.htm

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star schema - In data warehousing and business intelligence (BI), a star schema is the simplest form of a dimensional model, in which data is organized into facts and dimensions. A fact is an event that is counted or measured, such as a sale or login. A dimension contains reference information about the fact, such as date, product, or customer. A star schema is diagramed by surrounding each fact with its associated dimensions. The resulting diagram resembles a star.

Star schemas are optimized for querying large data sets and are used in data warehouses and data marts to support OLAP cubes, business intelligence and analytic applications, and ad hoc queries.

Within the data warehouse or data mart, a dimension table is associated with a fact table by using a foreign key relationship. The dimension table has a single primary key that uniquely identifies each member record (row). The fact table contains the primary key of each associated dimension table as a foreign key. Combined, these foreign keys form a multi-part composite primary key that uniquely identifies each member record in the fact table. The fact table also contains one or more numeric measures.

For example, a simple Sales fact with millions of individual clothing sale records might contain a Product Key, Promotion Key, Customer Key, and Date Key, along with Units Sold and Revenue measures. The Product dimension would hold reference information such as product name, description, size, and color. The Promotion dimension would hold information such as promotion name and price. The Customer dimension would hold information such as first and last name, birth date, gender, address, etc. The Date dimension would include calendar date, week of year, month, quarter, year, etc. This simple Sales fact will easily support queries such as “total revenue for all clothing products sold during the first quarter of the 2010” or “count of female customers who purchased 5 or more dresses in December 2009”.

The star schema supports rapid aggregations (such as count, sum, and average) of many fact records, and these aggregations can be easily filtered and grouped (“sliced & diced”) by the dimensions. A star schema may be partially normalized (snowflaked), with related information stored in multiple related dimension tables, to support specific data warehousing needs.

Online analytical processing (OLAP) databases (data warehouses and data marts) use a denormalized star schema, with different but related information stored in one dimension table, to optimize queries against large data sets. A star schema may be partially normalized, with related information stored in multiple related dimension tables, to support specific data warehousing needs. In contrast, an online transaction processing (OLTP) database uses a normalized schema, with different but related information stored in separate, related tables to ensure transaction integrity and optimize processing of individual transactions.

See also: normalisation / normalization

[Category=Data Management ]

Source: WhatIs.com, September 2013 09:14:51, http://whatis.techtarget.com/glossary/Data-and-Data-Management