Understanding cube aggregations

Analysis Services uses a multidimensional space that consists of cells containing the data.

Since the data in Analysis Services is stored on the physical disk, running a query that affects cells on the lowest level can be slow. If you consider the cube in the previous picture, running a SELECT statement that aggregates the Internet Sales amount would access all the cells in the cube. However, you can pre-aggregate the data on frequently used levels of the different attributes. In the previous picture, aggregating on the Bikes level and or on the Year level can—together with relevant hierarchies—improve performance considerably.

In the FirstCube project that is built on the AdventureWorksDW2012 database, you can take the DimDate dimension as an example. The lowest level of the date dimension is on the day level. The date dimension then contains the month, quarter, and year attributes and a hierarchy defining their relationship.

The month level of the DimDate dimension...