Dimension Table

Dimension Table - In a star schema, a table which contains the data for one of the cube's dimensions.

The dimension table has a primary key which is used to connect it to the fact table.

The dimension table has one field for each level of each hierarchy contained in the dimension. The data values in these fields become the members of each of the dimension's levels.

The dimension table has as many attribute fields as possible. These fields describe individual characteristics of the dimension.

If there are multiple hierarchies in the dimension, there is one level field for each distinct level in each of the hierarchies. If the hierarchies share some levels in common, they are represented by a single field For Calendar and Fiscal hierarchies in a Time dimension, the level fields could be Fiscal Year, Calendar Year, Fiscal Quarter, Calendar Quarter, Month, and Day.

For the Product dimension table, some of the attribute fields could include Description, Product Number, Product Type, Department, Package Size, Weight, Shelf Length, etc.

The dimension tables in a star schema are intentionally de-normalized. The level fields and the attribute fields contain data that is duplicated in many of the records. This normally does not add a significant amount to the amount of storage space needed in the database, because the overall size of each dimension table is very small when compared to the size of the fact table.

[Category=Data Warehousing ]

Source: SDG Computing Inc., 07 May 2010 07:53:57, SDG Computing, now offline

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Dimension Table - A table that contains discrete values (usually a countable text field like school or degree). Also see fact table. Imagine viewing a spreadsheet. The row and column names would be the dimensions and the numeric data within would be the facts.

[Category=Data Warehousing ]

Source: Aexis Business Intelligence, 28 November 2010 13:43:52, http://www.aexis.eu/DataWarehouse-Glossary/

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Dimensional Table - Dimension tables store records related to this particular dimension. No facts are stored in a dimensional table.

[Category=Data Warehousing ]

Source: Aexis Business Intelligence, 29 November 2010 08:03:21, http://www.aexis.eu/DataWarehouse-Glossary/

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dimension table - A dimension table is a table in a star schema of a data warehouse. A dimension table stores attributes, or dimensions, that describe the objects in a fact table.

In data warehousing, a dimension is a collection of reference information about a measurable event. These events are known as facts and are stored in a fact table. Dimensions categorize and describe data warehouse facts and measures in ways that support meaningful answers to business questions. They form the very core of dimensional modeling.

A data warehouse organizes descriptive attributes as columns in dimension tables. For example, a customer dimension’s attributes could include first and last name, birth date, gender, etc., or a website dimension would include site name and URL attributes.

A dimension table has a primary key column that uniquely identifies each dimension record (row). The dimension table is associated with a fact table using this key. Data in the fact table can be filtered and grouped (“sliced and diced”) by various combinations of attributes. For example, a Login fact with Customer, Website, and Date dimensions can be queried for “number of males age 19-25 who logged in to funsportsite.com more than once during the last week of September 2010, grouped by day.”

Dimension tables are referenced by fact tables using keys. When creating a dimension table in a data warehouse, a system-generated key is used to uniquely identify a row in the dimension. This key is also known as a surrogate key. The surrogate key is used as the primary key in the dimension table. The surrogate key is placed in the fact table and a foreign key is defined between the two tables. When the data is joined, it does so just as any other join within the database.

Like fact tables, dimension tables are often highly de-normalized, because these structures are not built to manage transactions they are built to enable users to analyze data as easily as possible.

Related glossary terms: HP e3000, fact table, JAR file (Java ARchive), Create, Read, Update, Delete (CRUD) Cycle, OLAP cube, customer data integration (CDI)

[Category=Data Management ]

Source: WhatIs.com, 28 July 2013 09:23:30, http://whatis.techtarget.com/glossary/Data-and-Data-Management