Dimensional Modeling - Cube (Olap Cube)

> (OLAP|Analytic) > Dimensional Modeling - Dimensional Schemas

1 - About

Dimensional modeling concepts are applicable wither implementing the model in a cube or a relational database. The only differences are in physical implementation. Cubes is a term that is more used in the multidimensional database field.

It can be thought of as extensions to the two-dimensional array of a spreadsheet. For example a company might wish to analyze some financial data by product, by time-period, by city, by type of revenue and cost, and by comparing actual data with a budget. These additional methods of analyzing the data are known as dimension. Because there can be more than three dimensions in an OLAP system the term hypercube is sometimes used.

The term cube is used because it describes the multidimensional nature of the data, as opposed to the one-dimensional or two-dimensional nature of relational tables. However, almost all cubes have more than three dimensions.


3 - Functionality

The OLAP cube consists of numeric facts called measures which are categorized by dimensions. The cube metadata may be created from a star schema or snowflake_schema of tables in a relational database. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables.

4 - Documentation / Reference