A global financial institution is implementing data masking technology to protect personal data used for testing purposes in non-production environments. Which of the following is the GREATEST challenge in this situation?
Data masking tools being complex sounds familiar, but I wonder if the implementation difficulty is really the main concern compared to the others listed.
I feel like identifying personal data across systems could be really tough, but I can't recall if it’s the greatest challenge mentioned in our practice questions.
Data masking tools can be complex, but I think option B is the biggest hurdle here. Maintaining the integrity of the data relationships is critical for effective testing, so that's probably the greatest challenge.
I'm leaning towards option C. Identifying all the personal data across the interconnected systems could be really tricky, especially in a large global institution. Gotta make sure you don't miss anything.
Hmm, I'm not sure. Option A about access control in dev/test environments also seems like a major challenge. Protecting sensitive data in those less secure environments is crucial.
This one seems pretty straightforward. I'd say the biggest challenge is option B - retaining the complex relationships within and across systems for testing purposes while also masking the personal data.
Ah, the Communications Management Plan - that's not one of the typical models, is it? I'm pretty sure that's not used to define assurance requirements.
Okay, I've got this. The key is to identify the plan that is specifically focused on creating and maintaining retrievable copies of information. That narrows it down to either the Disaster Recovery Plan or the Data Backup Plan.
Hmm, this is a tricky one. I'm a bit fuzzy on the default behavior of in.mpathd and how it selects test partners. I'll need to review my notes on IPMP configuration to make sure I choose the right answers.
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