Informatica Persistent Data Masking Review

Data transformation and test management features allow us to work with unstructured data

What is our primary use case?

We provide services mostly to banks. 

I am currently working at a bank where they are using Data Masking and Data Transformation at the same time. They are an old core banking system, which is COBOL, and it's unstructured data. We are using Data Transformation to transform and structure the data into a relational format.

We use the test data management to create test data from the relational data. To create the test data, we mask using different techniques for the discovery. After that, we re-transform the relational data into unstructured data to be fed into the core banking system.

What is most valuable?

The most valuable feature is data discovery. This is the most exciting feature for all of the banks.

What needs improvement?

I have encountered some issues using the substitution, which is one of the techniques of data masking. I used the substitution and software. I had issues in both when using the field, and specifying the field. Each one will have the same data for the same person, and they will have realistic data each time. This issue was raised with technical support and it was flagged as an issue that had no solution. They have indicated that it is a bug that would be resolved in the next release.

In the next release, I would l like to see the bug with the substitution resolved.

For how long have I used the solution?

I have two years of experience with Informatica Data Masking.

What do I think about the stability of the solution?

This solution is stable and we have not had any issues.

What do I think about the scalability of the solution?

Informatica Data Masking is scalable.

How are customer service and technical support?

The technical support is good, although sometimes they don't respond quickly. Overall, they are good.

I raised the case where I was having some issues with the substitution, and it took two months. Finally, the answer was that they have no solution for this, but said they will flag it as a bug to be resolved for the next release.

As I was not able to stop the project because of the bug, I created a workaround using PowerCenter to make it work. The data was not unique. I used PowerCenter and added an ID to all of the columns, then I concatenated the ID with the columns. As an example of why this was complete is if my name is Donna, it will show as Donna123. That way, any other person named Dana in the same database or table would show as Donna246 and they would no longer be the same. With this, I would then offer a substitute.

Which solution did I use previously and why did I switch?

Previously, we did not use another solution.

How was the initial setup?

The initial setup is straightforward.

The length of deployment depends on the solution. For example, I find security was very easy, but the data integration was more complex. This is because it has many features and you can do many things. Setting up the data quality was also very easy.

We have deployed both on-premises and on the cloud. Mostly, I work in Lebanon and some  Arab countries also. There have been some issues with the Cloud, so they prefer on-premises software. We implemented some iPaas on the Cloud for Data integration.

What other advice do I have?

It's good as a solution.

I would rate this solution a nine out of ten.

Which deployment model are you using for this solution?

**Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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