Multidimensional Data Model - Data Warehouse

Multidimensional data model

A data warehouse is based on the multidimensional data model which views data in the form of a data cube.
A data cube allows data to be modeled and viewed in multiple dimensions.

It is defined by dimensions and facts.

  • Dimension tables are perspectives or entities with respect to which an organization which wants to keep records.
  • For example, "All Electronics" Company may create a sales data warehouse to keep records of the store’s sales with respect to the dimensions time, item, branch, and location. 

Dimension Table

These dimensions allow the store to keep track of things like monthly sales of items and the branches and locations at which the items were sold.

Each dimension may have a table associated with it, called a dimension table.

For example, a dimension table for item (item_name, brand, type), or time(day, week, month, quarter, year), branch, and location.

Dimension tables can be specified by users or experts, or automatically generated and adjusted based on data distributions.

Fact Table

A multidimensional data model is typically organized around a central theme, like sales, for instance. 

This theme is represented by a Fact table.
Facts are numerical measures.

Think of them as the quantities by which we want to analyze relationships between dimensions. 

Examples of facts for a sales data warehouse include dollars sold (sales amount in dollars), units sold (number of units sold), and the amount budgeted.

The fact table contains measures (such as dollars_sold) and keys to each of the related dimension tables.

Data Cube

A data cube, such as sales, allows data to be modeled and viewed in multiple dimensions.

Suppose ALLELETRONICS create a sales data warehouse concerning dimensions.

  • Time
  • Item
  • Location
  • Supplier

Note: we may display any data n-D data as a series of (n-1)D “cubes”.

3-D Data Cube

Multidimensional data model 
In data warehousing literature, an n-D base cube or the cuboid that holds the lowest level of summarization is called a base cuboid. 

The topmost 0-D cuboid, which holds the highest level of summarization, is called the apex cuboid. 

The lattice of cuboids forms a data cube. 

The figure shows a lattice of cuboids forming a data cube for the dimensions time, item, location, and supplier.

A Lattice Of Cuboids

Multidimensional data model

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