Getting Practical and Tactical with Safe Data

Published by Privitar

Most organizations know how important it is to protect data for analytics, but knowing the importance doesn’t mean that actually doing this is easy. There is no silver bullet to making data safe, nor is there one single source of truth that provides all the desired outcomes for all data types, in all use cases. Safeguarding data is a contextual challenge so different approaches are needed depending on the context – the data, the use case, the user. So how can an organization build out safe data pipelines, decide which methods of protecting data are right for their organization, and get started or advance in their use of safe data for analytics and insights?

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