IBM InfoSphere Optim Test Data Management (TDM) Reviews

I really appreciate using the match keys and comparing the records before and after masking. This is done by joining multiple tables to form a single record. This helps to get a faster validation of data.

The product has helped to streamline the Test Data Management (TDM) process. Without this product, participation from several stakeholders such as DBAs, Admins, and the Environment refresh team were required.

Scripting complex data masking requirement in Lua can be converted into a simpler, user-friendly interface.

Instead of a free text editor, which is used to code the functions (mostly "if-else" conditions), a drop-down like interface can be created to join various conditions and generate a policy for masking.

I have used the product for three years.

We have not encountered any issues with respect to stability.

We faced some challenges with a combination of complex referential integrity and a higher volume of data.

We have enjoyed excellent technical support.

IBM Optim was the first solution that we used.

This response is specific to a z/OS environment. The initial setup is complex and requires assistance from mainframe administrators.

The initial setup should be made simpler with a step-by-step or a one-click installation guide.

Pricing and licensing is higher compared to other products.

We evaluated and compared three other COTS TDM solutions.

I recommended that others complete a PoC/pilot before starting an implementation. Some of the diverse technology landscape might require a hybrid Test Data Management solution.

Data masking with consistency across databases and applications is the most valuable feature.

We only do data masking as of now because it is a compliance requirement. However, the benefits in sub-setting have not been realized yet. No application has availed of the service.

Licensing could be improved. The PVU licensing mechanism is a limiting factor to expanding the use of the tool.

I have been using IBM Optim for five years.

We did have some stability issues.

We did have some scalability issues.

I would give technical support a rating of 7/10.

We did not have a previous solution.

The setup was complex for me, because I am not familiar with ODBC. I have to learn how to use it, in order to connect to different databases.

Discuss the PVU limitations when it comes to extending the service with new apps.

I have no idea if our architecture team looked at alternatives. I started to use the tool as developer.

There are many flavors of Optim. Make sure you understand what you want.

• Optimizing and automating recurring processes that create and manage non-production environment data.
• Creating right-sized fictionalized test databases.
• Protecting sensitive data in non-production environments: Sensitive data such as national IDs, credit card numbers, email addresses and confidential corporate information can be masked to protect it from misuse and fraud.

This product allowed us comprehensive test data management capabilities for creating right-sized, fictionalized test databases and it accurately provides subsets of referential intact data.

We have been using this solution for six years.

IBM Optim TDM is quite stable. We have never had any stability problems.

IBM Optim solutions are highly scalable. We have never had any scalability issues.

I rate level of technical support a good 7/10.

We didn't use any different solution before.

Initial setup is a little bit complex.

Pricing and licensing models may vary depending on the server infrastructure.

Before choosing this product, we also evaluated Informatica Test Data Management and Oracle Data Masking.

Optim Test Data Management and Privacy solutions help you to create right-sized test databases, automate test processes and mask sensitive data to protect privacy, maximize the accuracy of testing using production data for test purposes.

The Data Archive or Data Growth feature is one of the very useful solutions that help organizations to manage and support their database archiving strategies. This feature also enables business policies, data retention and access control.

This feature helps organization to plan test data strategies based on data retention policies.

In the IBM Optim tool, the Synthetic Test Data Generation feature is lagging behind.

We have not encountered any stability issues.

We have not encountered any scalability issues.

• Data growth solution
• Data masking and test data management
• Data decommission

The tool does not support new test data generation.

Optim tool is helpful to extract (subset and mask) the data from a production-like environment. The test data generation is not part of IBM Optim.

I have used it for three years.

Sometimes, we have had deployment issues.

Only very rarely have we encountered stability issues.

Customer service is good.

Technical support is not bad.

The latest version of Optim with designer and manager are quite complicated, but this includes various features.

I value data masking, data extraction/sub-setting, data comparison, and data load.

• Creates an automated process for production data extraction
• Does scrubbing
• Does sub-setting and movement of data
• Tests regions across various platforms including legacy and distributed platforms

The tool needs to have more test data management features like synthetic data generation and data reservation.

Optim is capable of extracting/masking production data and move it to the test region, for test data provisioning. However, there are various scenarios when the production data, cannot fully meet the testing requirements. In such cases, the testers have to manually set up the data, as Optim does not provide any functionality, to generate data from scratch. Hence, synthetic data generation is a very important feature, that must be present in a TDM tool. Other tools such as CA TDM have this feature.

There are other important TDM features, that are missing from IBM Optim such as:

• Data reservation that provides ability to the data user, in order to reserve certain data, so that no one else uses the same data for testing.

• Data mining that provides a capability to search for data, that matches the test requirements.

I have used the product for three years.

I did not encounter any stability issues.

I did not encounter any scalability issues.

I would give technical support a rating of 7/10.

In the past, in-house scripts were being used for production data extraction/masking. We moved to Optim to utilize an industry standard tool to enable the entire enterprise to use a consistent solution for synchronous data refresh across applications.

The initial setup was easy, but time consuming. There is a lot of one time development effort involved to setup and implement the Optim based automated process.

I cannot comment on pricing as it varies for each customer and agreement with IBM.

Other options were evaluated including tools like CA Test Data Manager.

Optim is a great tool for enterprise data movement, data masking, data sub-setting, data comparison, and data aging.

However, it lacks certain capabilities critical for central test data management operations like data generation. The requirement scope/goal should be clearly defined before selecting the tool.

• Data masking
• Test data environment setup and management

Makes it really easy to obfuscate big tables involving lots of columns and to manage 100’s of tables without putting in much effort.

Data masking with InfoSphere Optim products creates intermediary extract files and writing the data to persistent storage, which means that extraction, masking, and insertion happen being separate processes, taking more for the process to run.

I have used IBM InfoSphere Optim for five years.

We have not had any stability problems.

We have had some scalability issues.

We previously used IBM DataStage. There is a lot less flexibility in the InfoSphere DataStage Pack compared to the InfoSphere Optim products for selecting a specific subset of data to be masked. DataStage is driven by supplied SQL statements, whereas InfoSphere Optim is driven by traversing the database model and picking up related data elements from a starting point. Optim has more data privacy options.

Initial setup was a bit tedious and time consuming.

It’s very helpful in the mainframe environment.