Histograms are an important tool in data analysis. They represent the distribution of frequencies of an entity or event. In OLAP, those terms translate to dimensions and their attributes.
This recipe illustrates how to implement histograms over existing attributes.
In order to create them, we need a measure which counts distinct members of an attribute for any given context.
There are two solutions to this problem. One is to use the calculated measure; the other is to use a regular measure with the distinct count type of the aggregation.
Naturally, many BI developers lean towards the first option. Undoubtedly, it is a much faster-to-implement solution because deploying ...