A multidimensional data diagram provides a graphical view of your datamart or data warehouse database, and helps you identify its facts, cubes and dimensions.
Numeric values or measures such as sales total, budget limits, are the facts of the business. The area covered by a business, in terms of geography, time, or products are the dimensions of the business.
The multidimensional diagram is used to design the cubes in an OLAP engine, together with the different analysis dimensions.
Business analysts use OLAP databases to send queries and retrieve business information from the different dimensions existing in the database.
OLAP databases are populated with data from a data warehouse or data mart database. This data transfer is implemented via a relational to multidimensional mapping, the data warehouse or data mart database being the data source of the OLAP database. The OLAP cube is designed to support multidimensional analysis queries, it is organized according to user-defined dimensions.
Multidimensional analysis queries usually involve calculated lists, such as growth and decline rates and time-based comparisons. They aim at detecting trends and relationships. These types of queries are supported by an OLAP database, but not by an operational database.
For more information on the relational to multidimensional mapping, Core Features Guide > Linking and Synchronizing Models > Object Mappings > Mappings between Operational, Data Warehouse, and OLAP Databases.
Example
Sales data can have the dimensions product, region, customer, and store. Facts, for example, the sales totals, are viewed through the user-defined dimensions. When you retrieve the sales total of a particular product for a particular region, you are viewing the sales total through the product and region dimensions. The most common dimension is time because the purpose of multidimensional analytical queries is to find trends.
