Transformation Summary in SAP data service ( BODS) - Part1 - Validation and Case Transformation

[pallab_haldar]

Today I am going to discuss different Transformation scenarios in SAP data service ( BODS) which is required for transformation in Dataflows.

1. Validation Transformation :

This Transformation is used to validate data. It filters the data based on the validation rule. If passed the rule, go to one target, If it fails go to another target set to deliver the failed items. If the data fails and violates the rule the the rule or failed condition goes to another target based on the scenario.

We need to create a validation rule on the validation transformation based on that it filters the data and sends it to the destination you mentioned in the target.

There is a standard project structure that we will use for all of our transformation and given below -

 

For example, if the Datastore of the source table consists of the below rows -

 

 

Sample DF Diagram for Validation Transformation :

 

 

 

 

 

In the PS1 table (set to get Passed) -

in fl1 table ( set to get Failed) -

 

Validation transformation filters the data based on certain conditions and sends the data to different targets based on rule validation.

2. Case Transformation: Similar to like case statement in JAVA, HANA, and ABAP. You can direct your source data row into multiple(N numbers of direction) targets based on different conditions.

For example, if the Datastore of the source table consists of the below rows -

Sample DF Diagram for Case Transformation :

Here we will apply 3 conditions on the case statement and if Cond 1-> Passed   ->CUST1, Cond 2-> Passed   ->CUST2, and Cond 3-> Passed   ->CUST3

CASE 1:  CUST.CREDIT_AMOUNT  > 400000

Case  2: CUST.CREDIT_AMOUNT  > 300000

Case 3: CUST.CREDIT_AMOUNT  > 1000000

Put all the conditions similar to be below one by adding cases :

As a result :

 

1. CUST1 table generated with the below 3 entities :

 

2. CUST-2 table generated with the below 1 entities :

 

 

2. CUST3 - table generated with the below 2 entities :

 

# What is the difference between Validation and Case transform and which scenario we will use each transformation? which we will used to develop a better, cost effective and faster dataflow design ?

The execution time difference between the Case and Validation transforms is probably very very small. But the target limits two main tables/files based on fail and pass. Case can use for route the data to multiple target based on different case.

In some business scenario , the load failed reason required by business as a log. The Validation transform can gather statistics about the validation process and very useful in that scenario.