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Hi All,
I have 2 metrics (2 Facts QVDs) which has different data structure and formats. The DATE fields have different definition though in both QVDs and granularity is different as well.
QVD 1 is at Month_Year and Supplier level.
QVD 2 is at Plant, Month_Year and Supplier level.
For example,
QVD 1 has: Month_Year, Supplier_ID, Date_ID, Order Date, Promise Date, Receive Date, KPI1
QVD 2 has: Plant_ID, Month_Year, Supplier_ID, Date_ID, Order Amt, Order Qty, Calendar_ID, KP2.
As a best practice approach, all the Facts to be concatenated into a single table. Looking into my above scenario, could someone please help, Which approach to follow - CONCATENATE (How) or JOIN?
Regards!
Hi,
A concatenate load will append the data from table 2 to table 1, combining the common fields. If it finds a field which isn't in both tables, it simply loads as blanks in the respective table. This sounds like what you need, this will create 1 main fact table of the two tables combined.
Joining will add columns to your fact table instead of rows.
I would absolutely concatenate the two fact tables. But you will need Generic Keys to do it properly. Read more here:
Fact Table with Mixed Granularity
HIC