Hi All
Thanks for your reply.
Let me put some more details to explain my scenario.
As mentioned in my post my data selection criteria has multiple input criteria (company codes, Profit center, Date Range) based on which I need to extract initial data and then summarize them based on diff criteria
Assume this to be my UI data selection criteria.
.
Section 1 :Summarize data by Material
Output like :
[
{ "MATNR" :"1mk888888", "Amt": "450.20 " },
{ "MATNR" :"234k888888", "Amt": "150.20 " },
{ "MATNR" :"7888888888", "Amt": "250.20 " },
]
Section 2: Summarize data by Document type
Output like:
[
{ "DOCTYPE" :"PE", "Amt": "345678 " },
{ "DOCTYPE" :"XE", "Amt": "945678 " },
{ "DOCTYPE" :"YE", "Amt": "745678 " },
]
Section 3: Summarize by Profit center.
Output Like:
[
{ "PRCTR" :"PC01", "Amt": "307838 " },
{ "PRCTR" :"XC01", "Amt": "995678 " },
{ "PRCTR" :"UC01", "Amt": "305678 " },
]
Section 4: Summarize by F Year.
Output Like:
[
{ "FYEAR" :"2010", "Amt": "3679002 " },
{ "FYEAR" :"2011", "Amt": "7679002 " },
{ "FYEAR" :"2012", "Amt": "9679002 " },
]
All examples which i skimmed through SCN tend to concentrate on SO+SOITEM+PRODUCT as base example to explain expanded entity set which looks decent but with my scenario I am looking for more insight into correct approach for such scenarios where we may not have direct way to establish associations to leverage expanded entity set.
Appreciate your valuable feedback.