Protecting your customers begins with best practices for securely capturing, storing, and protecting the data you collect for or about them. When an organization has a large enough dataset, needs typically arise for doing analytical workloads or training machine learning models on this data. If you use random or mock data to generate a report or train a model, you arrive at an output that doesn’t reflect the true use case of the organization. Success on tasks like this seems to require production data.
Alternatively, perhaps production-like data is good enough. In this episode, I interview Alex Watson, co-founder and chief product officer at gretel. We discuss their solution for privacy preserving synthetic data that remains representative of the underlying dataset.
The post Privacy Engineering with Alex Watson appeared first on Software Engineering Daily.
By: SE Daily
Title: Privacy Engineering with Alex Watson
Sourced From: softwareengineeringdaily.com/2022/01/20/privacy-engineering-with-alex-watson/?utm_source=rss&utm_medium=rss&utm_campaign=privacy-engineering-with-alex-watson
Published Date: Thu, 20 Jan 2022 12:00:14 +0000
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