This can be useful e.g. if you are analyzing a survey where survey participants have rated statements with a score 1 to 5. With the .raw dimension you would be able to categorize data by score value.
The information we see here, is that the file contains in total 4,198 records, and that the Amount value of “55,2” appear in 24 of those records.
• Bill-to Name: This is a standard dimension that has been picked to be displayed along the vertical axis of the crosstab.
• Amount.sum: This is probably the most commonly used measure type. For Adventure Works, we can see that the total / summarized / aggregated value for Amount is 48,516.
• Amount.avg: This is the average value across all transactions. For Adventure Works, the average value is 693, which by the way is equal to Amount.sum divided by *.cnt (48,516 / 70).
• Amount.max: This is the maximum value across all transactions.
• Amount.min: This is the minimum value across all transactions.
• Amount.cnt: This is the distinct count of unique Amount values. For Adventure Works it is 49. Remember that e.g. the value 55,2 is present multiple times, but it is only counted as one here. This is why the Amount.cnt can be less than the total number of transactions (*.cnt = 70).
• Bill-to Name.cnt: Again, this is a distinct count, so unique appearances of Adventure Works will only count as 1 – as it will with any other customers in this crosstab. From the Total row, however, we may see that we have in total 78 distinct customers.
• *.cnt: Counts the total number of transactions for each dimension member. Adventure Works appear in 70 transactions.