SAP SuccessFactors – Scrambling Framework via Integration Center

[RajasekarVenkatachalaiah]

Business Case:

Instance refresh(snapshot) is a common routine in any industry to perform from Production instance to Lower instances (Dev, Test, Training, so on). This is applicable for most of the applications in the software world. The below topic provides insights on automating the anonymization process involved in SAP SuccessFactors to lower instance, by default there is very little offering from SAP on the anonymizing of data to lower instance. 

Why instance refresh is being done?

1. To ensure that Production config is in sync with other instances and ensures the new features/configuration is done on close to prod configuration and tested before moving it to production.
2. Easy to troubleshoot, as the prod issues can be replicated in lower instances, find the root cause and try the possible solution to fix the issue.

Process statement:

As all the production data is copied over to lower instance, it is important to anonymous the sensitive data in the lower instance before it is released for testers, country admin users and target systems. There is no or very little automation possibility available from SuccessFactors to anonymous the data from SAP SuccessFactors for very few fields. 

Here are the process steps involved.

• Export the data

• Extract the reports

• Export the csv template for each portlet

• Excel formulas to scramble identified sensitive info.

• Update each template with the scrambled info

• Import the updated template back into SF instance

• Post Refresh activities

And scrambling(anonymous) the data is very time consuming process especially incase the volume of records is more in the system. Until the lower instance is anoymized, the system will be locked.

Solution:

To mitigate the above problem, Integration Center came into rescue to automate the process of anonymization and also saved lot of manual efforts spent.

The Integration jobs for each portlet needs to created (one time activity) in Integration Center which requires anonymization. This eliminates below manual steps

1. Export the data
2. Extract the reports
3. Export the csv template for each portlet
4. Update each template with the scrambled info
5. Import the updated template back into SF instance

Here is the picture from demo system on how the jobs are created. I have intentionally not posted the scripts as it could vary from customer to customer. Creating Integration center jobs are straight forward and built on top of OData API, familiarize with OData dictionary, there are lot of blogs on the same.

Once the jobs are run successfully, data validation can be performed by exporting the data from the system. The above is a case study which saved weeks of effort for our team.

Hope this blog helps to automate your anonymization process. Thank you for reading!

@RajasekarVenkatachalaiah - Rajasekar Venkatachalaiah