Data warehouse dimension vs fact

  • What is a dimension vs measure vs fact?

    A measure is a numerical property of a fact that describes a quantitative attribute that is relevant to analysis.
    For example, each sale is measured by the number of units sold, the unit price, and the total receipts.
    A dimension is a property, with a finite domain, that describes an analysis coordinate of the fact..

  • What is fact and dimension in data warehouse?

    Facts and dimensions are data warehousing terms.
    A fact is a quantitative piece of information - such as a sale or a download.
    Facts are stored in fact tables, and have a foreign key relationship with a number of dimension tables.
    Dimensions are companions to facts, and describe the objects in a fact table..

  • What is fact and dimensions model?

    A dimensional model represents the different business processes of an organization.
    A fact table with its dimension table is a single business process.
    Each dimensional model consists of many fact tables, with each fact table joined with corresponding dimension tables..

  • What is fact dimension and measure in data warehouse?

    In data warehousing, facts and dimensions are standard terms.
    They inform us about things like the number of resources used for a particular task.
    They both store the exact measure of resources and details about the resource and task.Jun 22, 2021.

  • What is the data warehouse relationship between fact tables?

    Fact tables contain the content of the data warehouse and store different types of measures like additive, non-additive, and semi-additive measures.
    Fact tables provide the (usually) additive values that act as independent variables by which dimensional attributes are analyzed..

  • What is the difference between dimension column and fact column?

    A fact table holds the data to be analyzed, and a dimension table stores data about the ways in which the data in the fact table can be analyzed.
    Thus, the fact table consists of two types of columns..

  • What is the difference between measure and fact in data warehouse?

    A measure is a numerical value that indicates a business metric and is usually additive.
    You aren't restricted to a particular metric, either.
    Within a fact table, you can have numerous measures.
    If your fact table is used to track foreign purchases, for example, you might have measures for each sort of currency..

  • A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions.
    Commonly used dimensions are people, products, place and time. (Note: People and time sometimes are not modeled as dimensions.) A dimension table in an OLAP cube with a star schema.
  • Types of Dimensions in Data Warehouse
    Conformed Dimension.
    Outrigger Dimension.
    Shrunken Dimension.
    Role-playing Dimension.
  • Typically, dimension tables that are shared by multiple fact tables (or multiple dimensional models) are called shared dimensions .
    If shared dimensions already exist for any of the dimensions in the data warehouse or dimensional model, you should use the shared dimensions.
Facts and dimensions are data warehousing terms. A fact is a quantitative piece of information - such as a sale or a download. Facts are stored in fact tables, and have a foreign key relationship with a number of dimension tables. Dimensions are companions to facts, and describe the objects in a fact table.
The key differences between Fact and Dimension Tables are as follows: The Dimension table is a partner to the fact table and contains descriptive qualities that can be used as query constraints. The fact table includes measurements, metrics, or facts about business operations.

While facts correspond to events, dimensions correspond to people, items, or other objects. In the retail scenario used in the example, we discussed that purchases, returns, and calls are facts. On the other hand, customers, employees, items, and stores are dimensions and should be contained in dimension tables.

The two types of tables used in dimensional modeling are facts and dimensions. A dimension table contains descriptive attribute fields whereas a fact table contains only measures and key relationships. This is why requirements gathering is very important when building a data warehouse in its early stages.

A fact table is defined by its grain or most atomic level, whereas a Dimension table should be wordy, descriptive, complete, and of assured quality. The fact table helps to store report labels, whereas Dimension table contains detailed data. The fact table does not contain a hierarchy, whereas the Dimension table contains hierarchies.

Dimensions, on the other hand, are collections of reference information about the facts in a data warehouse. Dimensions categorize and describe the facts recorded in a data warehouse to provide meaningful, categorized, and descriptive answers to business questions.Generally, a numeric data field which is constant in nature and is not involved in calculations and measurements is considered to be a dimension while a data field which is involved in measurements and calculations is a fact. It depends on the designer for deciding the facts and dimensions.

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