New Ebook – SAP BODS Step by Step

Hi dear readers,

The ebook, SAP BODS step by step is now available on Amazon at just $2.99.

The book is invaluable for hands on experience and quick update of your skills to SAP Data Services.

SAP BODS is basically and ETL tool but has many more advantages over SAP BW. However, it still cannot replace SAP Standard BI extractors.

You will find BODS to be like a tool to extract and transfer records between two databases. Learning simple SQL for RDBMS will make it easy for you to understand BODS.

Here is the link for the Kindle ebook in US Amazon market, you can also get it in your local Amazon

Below is the link to buy the paperback version-

Case Transformation in SAP BODS

Case transform is a part of Platform set of Transform in data services. It deals with the branching logic i.e it separates source data into multiple output data sets based on a condition.

For example, the source data from different countries is diverted to separate country tables based on certain conditions.

The condition based on which the data is branched has two parts: Label and Expression.

The label is the path name to the target table and the expression has the SQL logic that separates the data.

For example, define a label Region_INDIA where expression is Employee.regionId = 1.

Here, Employee is the source table having regionId as a column.

To understand it more clearly, login to the data services. Create some sample data in Microsoft SQL Server like below: Continue reading →

Validation Transform in SAP BODS


A Validation transform is very much similar to the case transform. This also comes under ‘Platform’ set of transform in data services.

It is used to validate the data and transfer it to Pass and Fail tables. The validation rules can be defined in this transform. They can be simple or complex.

The rules can be written for each single column.

One important point to mention here is that a FAIL rule is stronger that PASS rule as a row will pass once it satisfies all the conditions but it will fail if any one of the condition is not satisfied.

A Validation transform has an input and two output schema.

In the Fail validation schema, there are two extra columns, one is Error Action and the other is Error Column.

The error action column will tell whether the  row is sent to pass or fail or both the schema.

The error column will have the information about which column has failed.

One extra table ‘Validation_RuleViolation’ will also be generated having the error details.

Also, there is option for ‘Action on Failure’. Here, you can direct the system to transfer the failed record to pass table, fail table or both the tables and also substitute a text in place of the failed column value.


Here, we will be using the same database as created in Case transform example.

Create a new project ‘validation_transform’. Continue reading →