Short note/Explain Multidimensional Data Model.

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 Multidimensional Data Model

  • Multidimensional data model stores data in the form of the data cube. Mostly, data warehousing supports two or three-dimensional cubes.
  • A data cube allows data to be viewed in multiple dimensions. Dimensions are entities with respect to which an organization wants to keep records. For example in-store sales records, dimensions allow the store to keep track of things like monthly sales of items and the branches and locations.
  • A multidimensional database helps to provide data-related answers to complex business queries quickly and accurately.
  • Data warehouses and Online Analytical Processing (OLAP) tools are based on a multidimensional data model.OLAP in data warehousing enables users to view data from different angles and dimensions.
  • Data warehouses and OLAP tools are based on a multidimensional data model which views data in the form of a data cube. A data cube enables data to be modeled and viewed in multiple dimensions. It is defined by dimensions and facts.

-  Dimensions are the perspectives or entities with respect to which an organization wants to keep records. The sales data warehouse may keep records of the store’s sales with respect to the dimensions time, item, branch, and location. Each dimension may have a table associated with it, called a dimension table. This table further describes the dimensions. For example, a dimension table for an item may contain the attributes item name, brand, and type.

- Facts are numerical measures that are used to analyze the relationship between dimensions. Examples of facts for a sales data warehouse include dollars_sold (sales amount in dollars), units_sold (number of units sold), and amount_budgeted. The fact table contains the names of the facts, or measures, as well as keys to each of the related dimension tables.

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