The data you import into a cube provides a snapshot of your business at a specific level of detail. For example, you might import your weekly or monthly sales for your surfboards in dollars for a specific city in which they were sold. The dimension elements that identify these data points are simple or leaf-level elements in each dimension. These data points can be surfboards sold in one week and in a particular city.
By using dimension hierarchies, you can easily aggregate numeric data into categories that are meaningful in your analyses. Each category corresponds to an aggregation of detail for two or more elements in a dimension. For example, you could create quarterly elements that sum monthly sales amounts. In TM1, elements that represent aggregations are called consolidated elements or consolidations.
We'll speak more about hierarchies later in this chapter.