A Multidimensional Data Model:: It is defined as a Data Model that allows data to be organized and viewed in multiple dimensions, such as time, item, branch, and location, enabling organizations to analyze relationships between different perspectives and entities efficiently.
A multidimensional data model views data in the form of a data cube, which allows data to be modeled and viewed in multiple dimensions. The key components are:
- Dimensions: These are the perspectives or entities concerning which an organization keeps records. For example, time, item, and location.
- Facts / Measures: These are the numerical measures or quantities. For example, sales amount.
Data Cube:: It is a multi-dimensional data structure. A data cube is organized by its dimensions (as Products, States, Date)
A data cube allows data to be viewed in multiple dimensions.
Example
A Retail store that wants to analyze its sales data. The dimensions could be:
- Time: Year, Quarter, Month
- Item: Product Category, Product Name
- Location: City, Store
Dimensions:
- Time: Q1, Q2, Q3, Q4
- Item: Electronics, Clothing, Groceries
- Location: New York, Los Angeles, Chicago