The majority of DAX measures will apply aggregating functions to numeric columns of fact tables. However, several of the most important metrics of a dataset are those which identify the presence of dimensions in fact tables such as the count of customers who've purchased and those who haven't. It can also be necessary to count the distinct values of a dimension column such as the number of postal codes sold to or the number of distinct marketing promotions over a period of time.
In the dataset for this project, the customer dimension table is exclusive to the Internet Sales fact table, and the measure should only count customers with internet sales history. Additionally, slowly changing dimension logic has been implemented so that a single customer defined by the Customer Alternate Key column could have multiple rows defined by the Customer Key column...