Integrating privacy into data systems might be difficult, but today it’s urgent. In an environment of rapidly changing regulations and increased public awareness, it’s essential that data professionals see themselves as the front line in ensuring privacy is protected — for both consumers and their organizations.
In Practical Data Privacy, Katharine Jarmul explains how data professionals can be proactive in responding to privacy demands and take the lead in putting privacy principles at the forefront of data science, machine learning, data engineering and data management.
Covering everything from data governance and anonymization to federated and encrypted learning, Practical Data Privacy bridges the gap between data science, engineering and security, and guides you through what’s happening at the cutting edge.
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