Normally, you would use measures on axes where actual values are to be displayed, such as, on the value axis of a bar chart, or as cell values in a cross table. Dimension columns, that is, attribute hierarchies and user hierarchies, can be used to split the viewed data into smaller subsets on categorical axes.

When you look at cube data in the Data in analysis flyout, you have the possibility to select one measure group and one related dimension at a time, which may help you selecting suitable options on the axes. The whole cube is treated as a single data table in Spotfire when you analyze it in-database.

There are also other implications of working with cube data. Since the measures are defined by the context of a dimension, it is not possible to create filters for measures.

When importing cube data, all cube aggregations are lost. Hierarchies are imported down to the leaf level and measure values for that level are retrieved. See Data Import more information.