Cross Joining Rows

user1759221

Using OBI 11g, How do I transform the following results from that in figure-1

in an Answer analysis to the one in figure-2?

Thanks in advance.

      

Initial Result   (Fig-1):
Product ID	Contact Type	Contact Date	Part Number	Part Order Date	100-Day Pre Order   Date	Pre-Order Cust.   Inq. Count
221	Cust. Inq.	02/11/2016
221	Cust. Inq.	02/17/2016
221	Cust. Inq.	03/01/2016
221	Part Order	02/15/2016	A6182	02/15/2016	11/07/2015
221	Part Order	04/20/2016	A6871	04/20/2016	01/11/2016
221	Cust. Inq.	03/21/2016
221	Part Order	05/14/2016	B1204	05/14/2016	02/04/2016
221	Cust. Inq.	05/25/2016
Desired Result   (fig-2):
Product ID	Contact Type	Contact Date	Part Number	Part Order Date	100-Day Pre Order   Date	Pre-Order Cust.   Inq. Count
221	Part Order	02/15/2016	A6182	02/15/2016	11/07/2015	2
221	Cust. Inq.	02/10/2016	A6182	02/15/2016	11/07/2015	2
221	Cust. Inq.	02/14/2016	A6182	02/15/2016	11/07/2015	2
221	Cust. Inq.	03/01/2016	A6182	02/15/2016	11/07/2015	2
221	Cust. Inq.	03/21/2016	A6182	02/15/2016	11/07/2015	2
221	Cust. Inq.	05/05/2016	A6182	02/15/2016	11/07/2015	2
221	Part Order	04/20/2016	A6871	04/20/2016	01/11/2016	4
221	Cust. Inq.	02/11/2016	A6871	04/20/2016	01/11/2016	4
221	Cust. Inq.	02/17/2016	A6871	04/20/2016	01/11/2016	4
221	Cust. Inq.	03/01/2016	A6871	04/20/2016	01/11/2016	4
221	Cust. Inq.	03/21/2016	A6871	04/20/2016	01/11/2016	4
221	Cust. Inq.	05/05/2016	A6871	04/20/2016	01/11/2016	4
221	Part Order	05/14/2016	B1204	05/14/2016	02/04/2016	5
221	Cust. Inq.	02/11/2016	B1204	05/14/2016	02/04/2016	5
221	Cust. Inq.	02/17/2016	B1204	05/14/2016	02/04/2016	5
221	Cust. Inq.	03/01/2016	B1204	05/14/2016	02/04/2016	5
221	Cust. Inq.	03/21/2016	B1204	05/14/2016	02/04/2016	5
221	Cust. Inq.	05/05/2016	B1204	05/14/2016	02/04/2016	5

[Deleted User]

I don't get what you are trying to achieve here. Repeat the 5 "Cust Inq" rows for each "Part Order" row?

The thing is you probably are trying to draw sth with pen & paper that's due to a messed up initial interpretation of a weird "requirement" and based on a data model that's also not made properly.