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sparsity
A concept that refers to multidimensional data in which a relatively high percentage of the combinations of dimension values do not contain actual data.
There are two types of sparsity:
Controlled sparsity occurs when a range of values of one or more dimensions has no data; for example, a new measure dimensioned by Month for which you do not have data for past months. The cells exist because you have past months in the Month dimension, but the cells are empty.
Random sparsity occurs when nulls are scattered throughout a measure, usually because some combinations of dimension members never have any data. For example, a district might only sell certain products and never have sales data for the other products.
Some dimensions may be sparse while others are dense. For example, every time period may have at least one data value across the other dimensions, making Time a dense dimension. However, some products may not be sold in some cities, and may not be available anywhere for some time periods; both Product and Geography may be sparse dimensions.
See also composite.