Data modelling and DAX
DISTINCTCOUNT over a high cardinality transaction ID is one of the most expensive things you can ask the storage engine to do. If you understand which of your dimensions have a functional dependency on that ID, you can answer a large share of your queries with a plain COUNTROWS instead, and shrink the work for the ones that are left.
This article aims to show how you can speed up distinct count calculations in Power BI using the built-in user-defined aggregations feature. The user-defined aggregation feature in Power BI is designed to work with direct query models and usually gets used for calculations such as SUM, MIN, MAX etc. However, it can also work well … Continue reading Speed up Distinct Count calculations in Power BI using Aggregations
Introduction For this blog, I want to share an interesting approach that can potentially speed up slow reports that include a distinct count calculation. The approach described in this article explains how you can add a DIY version of an approximate distinct count calculation to a DAX based model. The method combines a little pre-processing … Continue reading DAX : Approx Distinct Count
