OLAP cubes summarize raw business data to facilitate analysis of business performance. Cubes are organized in a multidimensional structure, defined by a set of measures (summarized business information, such as product sales) that are indexed by dimensions (business variables, such as time or location, on which the business facts depend).

This illustration shows a schematic representation of a cube that summarizes shipping data for a fictitious distribution company. The cube contains two measures: “Packages” represents the number of packages shipped and “Total Freight” represents the total shipping costs of those packages in a given quarter. The values of the measures depend on three dimensions: the shipping route, the regions to where packages are shipped (the “Destination” dimension), and the calendar quarter (“Time” dimension) in which the products shipped. Dimensions are made up of attributes, typically organized in hierarchies-the first and second quarter attributes roll up to the first-half hierarchy, for instance.

Online analytical processing (OLAP) cubes are typically built from a subset of data from a data warehouse and organized in a multidimensional structure, defined by a set of measures (summarized business information, such as product sales) which are indexed by dimensions (business variables, such as time or location, on which the measures depend). The illustration shows a simplified schematic representation of a cube that contains two measures (lower right) that might be used in a shipping application. “Packages” represents the number of packages shipped and “Total Freight” represents the total shipping costs of those packages in a given quarter. The values of the measures depend on three dimensions: the route by which the packages reach their destination, the locations where the packages are produced (the “Source” dimension), and the calendar quarter (the “Time” dimension) in which the packages shipped.

The granularity of the cube is determined by the unit value (or key attribute) along each of the dimensions. For example, along the Time dimension, the key attribute is calendar quarter. Each cell in the cube contains the values of the two measures for specific values of Route, Source, and Time. So, the cell in the lower left shows that 3,562 packages were shipped from South America by air in the first quarter. The total shipping costs of packages received from South America, by air, in the first quarter was $56,749.