Privitar adds enhanced capabilities for data protection and safe data analysis in the latest version of its data-privacy software

By Privitar - July 17, 2019

Privitar, whose software delivers the uncompromised data privacy that is essential for organizations worldwide to conduct safe and ethical data analysis, today released version 3.0 of its Publisher product, extending both its data-protection and safe data-analysis capabilities.

[London, United Kingdom / Boston, United States, 17 July 2019]

With Privitar Publisher 3.0, companies can use its centralized, policy-based approach to data privacy more widely within their organizations, automate more processes, and make data available to data scientists more quickly. Publisher 3.0 also enables companies to create richer and more valuable datasets for better data-driven insights, while retaining the privacy and security of sensitive personal information and comply with data protection regulations such as General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States.

Privitar CEO Jason du Preez said: "Leading companies have a heightened sense of urgency about safeguarding sensitive, personal information. They realize that customer expectations for data privacy are higher than ever and are taking proactive data-privacy measures to maintain customer confidence and trust.

"They're seeking to avoid the severe economic consequence, business disruption and brand erosion that accompanies a lapse in regulatory compliance."

Privitar Publisher 3.0 includes:

  • Publisher On Demand (POD), which is designed for organizations with heterogeneous data processing environments. It extends Publisher’s data protection capabilities to custom applications and data pipelines by providing them with APIs to apply policies and protect data ‘on-demand’. This enables flexible and consistent application of policies across data pipelines, including massive data in batch, streaming or on-demand online applications, regardless of whether platforms are on-premise, in the Cloud or hybrids.
  • SecureLink allows organizations to join datasets together in situations where they couldn’t do it before, due to regulations or trust boundaries. It helps the creation of richer and more valuable datasets for better data-driven insights, while retaining privacy and security. Linkable identifiers can be used to join together datasets held by different business units, regions or independent organizations while never disclosing them.
  • The Policy Manager Automation APIs give our customers the tools that they need to reduce the time needed to serve data requests, even when the datasets contain personal or sensitive data, by automating their data provisioning pipelines. Automated data privacy controls can be embedded in the data provisioning pipelines, reducing the need for human intervention and allowing custom applications and scripts by interacting with the Policy Manager via a set of REST API.

Ends

Press contact
For further information please contact:
Clementine Boyer Duroselle: cboyerduroselle@privitar.com

About Publisher 3.0
You can find further information about Publisher 3.0 on Privitar's website. You can also read the White Paper, the blog post and register for our webinars ‘How to automate your privacy protection (APIs)’ and ‘How to securely link datasets from different organisations (SL)’.

About Privitar
Privitar provides data-privacy software to companies and public sector organizations around the world to protect sensitive data and enable the safe and ethical use of data for insight. Privitar was established in 2014 with headquarters in London. The business expanded in 2018 and 2019, opening offices in New York, Boston, Paris, Munich and Singapore. Privitar raised $40m in a Series B funding round led by Accel in June 2019. Privitar also raised $16m in a Series A funding round in July 2017, with support from existing investors IQ Capital, 24 Haymarket and Illuminate Financial and new funding from Partech, CME Ventures and Salesforce Ventures.

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