In the KPMG revenue case (ICE #9), we first filtered observa…

In the KPMG revenue case (ICE #9), we first filtered observations for shipments made in 2017 and the “aggregated” sales transactions by TerritoryID, Shipping Month, and whether the sale is related to the new product (#7123).  We then outputted this data as a csv file. The grouped data has 5*12*2 = 120 observations.

In ICE#9 “join4” we combine the join3 table and the customer…

In ICE#9 “join4” we combine the join3 table and the customer master table using the variable CustID and an inner join. This results in a table with 1,168 observations. If we instead link this tables using a left join and the TerritoryID variable, we get a table with 18,937 observations. This increase in observations happens because TerritoryID does not uniquely identify observations in the customer master table.