Most of the reporting in BI applications needs the data to be reported period wise. So the built-in features of Rolling Sum and Rolling Average would be very useful.
In this example, we got the Sale Amount at the every beginning of the month, for example: 1st of July, 1st of August, 1st of September, etc,. At the other words, the day' data represents the whole week or month.
The following table was exported from Analyzer to excel. It simply explains the calculation and the differences of Rolling Sum and Rolling Average. Rolling Sum is very easy to understand. However, the Rolling Average is a little bit tricky. For example, Rolling Average YTD in October 2005 is $2619.20. We only have 4 days' events until October 2005, so the accumulated sum divided by 4. In a similar way, Rolling Average QTD and Rolling Average MTD are dividing this sum by the number of events measured during the quarter or month.