Introduction
From SAP BI 7.0 onwards, in DTP we have an option for semantic groups. We have different perception about Semantic Groups in DTP and its usage. Here I am summarizing specific usage of semantic group with examples.
Case 1. Calculation on group of records
Example: I would like to provide discount to each customer based on total sales value of Customer No, Country and Product category.
Discount should be assigned to each row i.e. for each product. I am having below sample records.
Product No | Customer No | Country | Product Category | Sale Value (In US $) |
P001 | C001 | US | Home | 5000 |
P002 | C002 | UK | Electronics | 3000 |
P003 | C003 | Germany | Kids | 2000 |
P004 | C004 | India | Home | 4000 |
P005 | C001 | US | Electronics | 1000 |
P006 | C003 | Germany | Kids | 6000 |
P007 | C005 | France | Home | 5000 |
P008 | C004 | India | Electronics | 3000 |
P009 | C002 | UK | Kids | 2000 |
P010 | C001 | US | Home | 1000 |
Discount Criteria based on Sales value as per grouping (Customer No + Country + Product Category)
Total Sales (In US $) | Discount % |
>=1000 AND <5000 | 5 |
>=5000 AND <10000 | 10 |
>=10000 | 20 |
Data Upload from PSA to Standard DSO.
DTP Package size is 5 Records.
End routine is calculating total sales which are used for discount calculation of each customer based on Sales value and assigning it to each product row.
Without Semantic Group Data Upload
Total sales value and Discount amount when data loaded without semantic group is as below
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sales (In US $) | Discount Amount (In US $) |
P001 | C001 | US | Home | 5000 | 5000 | 500 |
P002 | C002 | UK | Electronics | 3000 | 3000 | 150 |
P003 | C003 | Germany | Kids | 2000 | 2000 | 100 |
P004 | C004 | India | Home | 4000 | 4000 | 200 |
P005 | C001 | US | Electronics | 1000 | 1000 | 50 |
P006 | C003 | Germany | Kids | 6000 | 6000 | 600 |
P007 | C005 | France | Home | 5000 | 5000 | 500 |
P008 | C004 | India | Electronics | 3000 | 3000 | 150 |
P009 | C002 | UK | Kids | 2000 | 2000 | 100 |
P010 | C001 | US | Home | 1000 | 1000 | 50 |
Here if you notice about Customer C001 having same country and product category but Total sale is assigned as 5000 and 1000 respectively.
In such case for Product P010, customer received only 5% discount where as actually he/she should get 10%.
Similar case is for Customer C003 and product P003.
This is because Data uploaded into 2 equal packages of 5 records each, first 5 records into 1st package and rest 5 records in 2nd package.
Since in First package 5 records are as below,
Product No | Customer No | Country | Product Category | Sale Value (In US $) |
P001 | C001 | US | Home | 5000 |
P002 | C002 | UK | Electronics | 3000 |
P003 | C003 | Germany | Kids | 2000 |
P004 | C004 | India | Home | 4000 |
P005 | C001 | US | Electronics | 1000 |
Total Sales Value is calculated as below
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sale (In US $) |
P001 | C001 | US | Home | 5000 | 5000 |
P002 | C002 | UK | Electronics | 3000 | 3000 |
P003 | C003 | Germany | Kids | 2000 | 2000 |
P004 | C004 | India | Home | 4000 | 4000 |
P005 | C001 | US | Electronics | 1000 | 1000 |
So Discount values for first 5 rows are stored into Target DSO as below
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sale (In US $) | Discount Amount (In US $) |
P001 | C001 | US | Home | 5000 | 5000 | 500 |
P002 | C002 | UK | Electronics | 3000 | 3000 | 150 |
P003 | C003 | Germany | Kids | 2000 | 2000 | 100 |
P004 | C004 | India | Home | 4000 | 4000 | 200 |
P005 | C001 | US | Electronics | 1000 | 1000 | 50 |
For next 5 rows as below
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sale (In US $) | Discount Amount (In US $) |
P006 | C003 | Germany | Kids | 6000 | 6000 | 600 |
P007 | C005 | France | Home | 5000 | 5000 | 500 |
P008 | C004 | India | Electronics | 3000 | 3000 | 150 |
P009 | C002 | UK | Kids | 2000 | 2000 | 100 |
P010 | C001 | US | Home | 1000 | 1000 | 50 |
With Semantic Group Data Upload
Key fields are Customer no, Country and Product category
Total sales value and Discount amount when data loaded with semantic group are as below
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sale (In US $) | Discount Amount (In US $) |
P001 | C001 | US | Home | 5000 | 6000 | 500 |
P002 | C002 | UK | Electronics | 3000 | 3000 | 150 |
P003 | C003 | Germany | Kids | 2000 | 8000 | 200 |
P004 | C004 | India | Home | 4000 | 4000 | 200 |
P005 | C001 | US | Electronics | 1000 | 1000 | 50 |
P006 | C003 | Germany | Kids | 6000 | 8000 | 600 |
P007 | C005 | France | Home | 5000 | 5000 | 500 |
P008 | C004 | India | Electronics | 3000 | 3000 | 150 |
P009 | C002 | UK | Kids | 2000 | 2000 | 100 |
P010 | C001 | US | Home | 1000 | 6000 | 100 |
In this case records will be grouped based on Semantic key definition and even if there are 2 packages each will have records as below.
Records in First package grouped based on are Customer No, Country and Product Category
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sale (In US $) | Discount Amount (In US $) |
P001 | C001 | US | Home | 5000 | 6000 | 500 |
P002 | C002 | UK | Electronics | 3000 | 3000 | 150 |
P005 | C001 | US | Electronics | 1000 | 1000 | 50 |
P009 | C002 | UK | Kids | 2000 | 2000 | 100 |
P010 | C001 | US | Home | 1000 | 6000 | 100 |
Records in Second package
Product No | Customer No | Country | Product Category | Sale Value (In US $) | Total Sale (In US $) | Discount Amount (In US $) |
P003 | C003 | Germany | Kids | 2000 | 8000 | 200 |
P004 | C004 | India | Home | 4000 | 4000 | 200 |
P006 | C003 | Germany | Kids | 6000 | 8000 | 600 |
P007 | C005 | France | Home | 5000 | 5000 | 500 |
P008 | C004 | India | Electronics | 3000 | 3000 | 150 |
Due to this semantic grouping we have correct values for the Total Sales and our discount values are also calculated as expected.
Please note to accommodate records as per semantic group, package size will be automatically adjusted. Hence, it will not be constant through out the load.
Case 2. Error handling
Similarly if Error handling is enabled and error DTP is available, error handling functionality will work as below based on semantic group.
Without Semantic Group Data Upload
In case there is an error in the record having product no P001 then it will go into error stack and rest of the records will be uploaded. In such case for Product P010, total sales value will be 1000 and hence discount will be 5% i.e. 50$.
Even later if we will correct first record (P001) into error stack and upload it through error DTP, Discount value will not change for record P010.
With Semantic Group Data Upload
In case there is an error in the record having product no P001 then it will go into error stack along with record having product id P010 and rest of records will be
uploaded into target. It is due to semantic definition, so even one record is having error, both records are transferred into error stack to maintain semantic grouping.
In such case, when product P001 will be corrected into error stack and error DTP will run, it will upload both records with correct total sales and discount value.
Additional Note
Here I have used only 2 cases for illustration purpose. In real life there can be more use cases as per specific needs.
Please note above example is to explain the concept of semantic groups. There can also be other ways to achieve this calculation.
Hope it will help to get better insight about semantic groups into DTP for beginners.