Time Series using different keys

Question

Hi, i'm currently using the time series algorithm to do some forecasting on some data.
My data looks like this :
Date                     City               CustomerID         Sales
2003-12-01       New York              12346               45
If i only specify the date as a key time. I can forecast the total sales.(because i am using a cube who aggregates all the data)
But my goal is to forecast sales for each city and/or for each customer.
I tryed to make a cube with date and customer id as keys, but time series isn't compatible with that type of data as a key sequence.
I tryed doing nested tables not working(altough i might do something wrong).
How can use the field date as a key sequence and specify a key like customer id to do forecast the sales / customers?

Answer 1

Hi O G-M,
Each model must contain one numeric or date column that is used as the case series, which defines the time slices that the model will use. The data type for the key time column can be either a datetime data type or a numeric data type. However, the column must
contain continuous values, and the values must be unique for each series. The case series for a time series model cannot be stored in two columns, such as a Year column and a Month column. For more information about it, please see:
http://msdn.microsoft.com/en-us/library/ms174923(v=sql.100).aspx
Thanks,
Eileen
Eileen Zhao
TechNet Community Support