🔏 Restrictive Condition

The indicator constraints reduce the dimensionality of the dataset and hence the complexity of data analysis by performing slicing, dicing, and combining slices on multidimensional datasets.

For example, as demonstrated in the figure below, the source dataset has three dimensions: time, product, and region. If a certain indicator is set with a constraint such as time equals 2004, then the dimensionality of the dataset associated with this indicator (after dimensionality reduction, which is not physically stored) reduces to two dimensions: product and region.

When defining indicators, dimensions that are not set with constraints can be designated as "Free Dimensions." This explicitly informs users about the available dimensions of the dataset after dimensionality reduction. However, this is not mandatory, and users can still choose to analyze using any dimension.

For detailed settings of constraints, refer to the Slicer documentation.

For indicators using SQL models, combination slicers can be set up to implement complex constraints. For details, refer to the Combination Slicer documentation.