For DevOps, data needs to be made available to users in order to do bug fixes and software improvements. However, when that data is sensitive, it is risky to make that available to a broad group of users who could either be internal or third parties.
How can technology reduce the risk of using sensitive data for DevOps?
Publisher can de-identify sensitive data and make it useful for DevOps scenarios. Our privacy algorithms can preserve the richness and referential integrity of the dataset. This means de-identified data has higher quality than data from synthetic generators.
Data Privacy for DevOps Brief
Learn how you can quickly and securely provision valuable data to DevOps environments
Why you really don't need production data for Test and Dev
We’re living in the age of big data, but without a way to securely provision to Analytics, Machine Learning and Test and Dev environments, many organisations still aren’t feeling a big difference..
The 6 principles of privacy-safe Test and Dev data
Download here our checklist. It lays out six principles to follow to ensure your data is both safe and useful for Test and Dev purposes.
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