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PeerSpot user
Product & Project Manager at a tech services company with 51-200 employees
Consultant
May 10, 2017
Automates recurring processes that create and manage non-production environment data.
Pros and Cons
  • "IBM Optim solutions are highly scalable."

    What is most valuable?

    • 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.

    How has it helped my organization?

    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.

    For how long have I used the solution?

    We have been using this solution for six years.

    What do I think about the stability of the solution?

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

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    What do I think about the scalability of the solution?

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

    How are customer service and support?

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

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

    We didn't use any different solution before.

    How was the initial setup?

    Initial setup is a little bit complex.

    What's my experience with pricing, setup cost, and licensing?

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

    Which other solutions did I evaluate?

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

    What other advice do I have?

    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.

    Disclosure: My company has a business relationship with this vendor other than being a customer.
    PeerSpot user
    PeerSpot user
    Senior Project Manager /Senior Solution Architect at Cognizant
    Real User
    May 8, 2017
    The Data Growth feature enables business policies, data retention and access control.
    Pros and Cons
    • "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."
    • "In the IBM Optim tool, the Synthetic Test Data Generation feature is lagging behind."

    What is most valuable?

    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.

    How has it helped my organization?

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

    What needs improvement?

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

    What do I think about the stability of the solution?

    We have not encountered any stability issues.

    What do I think about the scalability of the solution?

    We have not encountered any scalability issues.

    Disclosure: My company does not have a business relationship with this vendor other than being a customer.
    PeerSpot user
    Buyer's Guide
    Test Data Management
    May 2026
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    it_user653673 - PeerSpot reviewer
    Works at a tech services company with 10,001+ employees
    Real User
    May 8, 2017
    Provides a data growth solution. Does not support new test data generation.
    Pros and Cons
    • "Customer service is good."
    • "The tool does not support new test data generation."

    What is most valuable?

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

    What needs improvement?

    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.

    For how long have I used the solution?

    I have used it for three years.

    What was my experience with deployment of the solution?

    Sometimes, we have had deployment issues.

    What do I think about the stability of the solution?

    Only very rarely have we encountered stability issues.

    How is customer service and technical support?

    Customer Service:

    Customer service is good.

    Technical Support:

    Technical support is not bad.

    How was the initial setup?

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

    Disclosure: My company has a business relationship with this vendor other than being a customer. My company is an IBM Premier Business Partner.
    PeerSpot user
    Technoloa76a - PeerSpot reviewer
    Technology Analyst at a tech services company with 10,001+ employees
    Real User
    Apr 23, 2017
    I value data masking, data extraction/sub-setting, data comparison, and data load.
    Pros and Cons
    • "Optim is a great tool for enterprise data movement, data masking, data sub-setting, data comparison, and data aging."
    • "The tool needs to have more test data management features like synthetic data generation and data reservation."

    What is most valuable?

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

    How has it helped my organization?

    • 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

    What needs improvement?

    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.

    For how long have I used the solution?

    I have used the product for three years.

    What do I think about the stability of the solution?

    I did not encounter any stability issues.

    What do I think about the scalability of the solution?

    I did not encounter any scalability issues.

    How are customer service and technical support?

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

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

    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.

    How was the initial setup?

    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.

    What's my experience with pricing, setup cost, and licensing?

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

    Which other solutions did I evaluate?

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

    What other advice do I have?

    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.

    Disclosure: My company does not have a business relationship with this vendor other than being a customer.
    PeerSpot user
    it_user599013 - PeerSpot reviewer
    Senior Test Analyst at a retailer with 1,001-5,000 employees
    Vendor
    Jan 31, 2017
    It has more data privacy options than older technologies. Initial setup was a bit tedious and time consuming.
    Pros and Cons
    • "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."

    What is most valuable?

    • Data masking
    • Test data environment setup and management

    How has it helped my organization?

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

    What needs improvement?

    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.

    For how long have I used the solution?

    I have used IBM InfoSphere Optim for five years.

    What do I think about the stability of the solution?

    We have not had any stability problems.

    What do I think about the scalability of the solution?

    We have had some scalability issues.

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

    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.

    How was the initial setup?

    Initial setup was a bit tedious and time consuming.

    What other advice do I have?

    It’s very helpful in the mainframe environment.

    Disclosure: My company does not have a business relationship with this vendor other than being a customer.
    PeerSpot user
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