You want to leverage sensitive data for analytics without compromising utility or compliance, but the range of data, users and purposes in your enterprise is vast and complex. Attempts at using only data masking or tokenization as a simple one-size-fits-all will fall flat.
The Privitar Data Privacy Platform™ meets the requirements for every context, enabling you to de-identify data by selecting from the full range of Privacy Techniques in any combination.
Analytics boils down to a series of questions asked to data. Protecting sensitive data for use in analytics requires you ask questions about context to balance risks with the need for data resolution and utility.
The Privitar Data Privacy Platform™ enables you to tune data resolution, helping you reduce re-identification risk in the specific context of each individual analysis, model or use.
Privitar provides more Privacy Techniques out of the box than any other technology, including data masking, tokenization, generalization, perturbation, redaction, substitution and encryption.
With the ability to apply multiple different Privacy Techniques to a single dataset, selecting from the full range in any combination, you get the flexibility to optimize for utility.
A mature approach to data privacy considers how to handle data later in its lifecycle. Re-identifying protected data with proper oversight is critical to some use cases, including healthcare intervention, customer experience or fraud prevention.
Privitar augments the full set of Privacy Techniques with the flexibility to decide when consistency, format and reversibility are preserved, so your data has the greatest possible utility throughout its required lifecycle.
Privitar delivers a unique platform that not only enables you to centrally define Privacy Policies and apply Privacy Techniques for any given context, but empowers you to manage protected data in Utility Optimized Datasets and track its use across all environments.
The Privitar Platform is the only solution designed to support advanced de-identification requirements, including Cross Entity Data Sharing and differential privacy, giving you the power to safely combine, share or release data.
The Privitar De-identification 101 series provides a ground-level introduction to the issues surrounding de-identification, one of the fundamental components of data privacy.Get Started
A successful data privacy strategy takes full account of data context. When you understand data context, you’re equipped to define protections that achieve the right balance of privacy and utility for your use case.Learn more
Our team of data privacy experts is here to answer your questions and discuss how data privacy can fuel your business.