Defending your prospects begins with finest practices for securely capturing, storing, and defending the info you acquire for or about them. When a company has a big sufficient dataset, wants sometimes come up for doing analytical workloads or coaching machine studying fashions on this information. Should you use random or mock information to generate a report or practice a mannequin, you arrive at an output that doesn’t replicate the true use case of the group. Success on duties like this appears to require manufacturing information.
Alternatively, maybe production-like information is nice sufficient. On this episode, I interview Alex Watson, co-founder and chief product officer at gretel. We talk about their resolution for privateness preserving artificial information that continues to be consultant of the underlying dataset.
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