Dealing with Empty Values in MDX Statements and Cubes

In Multidimensional Expressions (MDX) statements, you can look for empty values and then perform certain calculations on cells with valid (that is, not empty) data. Eliminating empty values when performing calculations can be important because certain calculations, such as an average, can be inaccurate if empty cell values are included.

If empty values may be stored in your underlying fact table data, and you do not want empty cell values appearing in your cube, you should create queries and data-modification statements that either eliminate empty values or coalesce empty values into some other value. Additionally, you can use the Null Processing option on a measure to modify null facts so that the null is converted into 0, converted to an empty value, or even throws an error during processing.