By Gerald Yong, Solutions Architect at Privitar

Data privacy is an important aspect of modern data provisioning, but it is not always easy to understand why it is needed and how it works.

Data privacy allows you to improve the utility of sensitive data by de-identifying it. Once it is de-identified, that data is made data safe so that it can be used for analytics and other use cases, and you can extract value and derive insights from that data. Otherwise, it would have to be locked because it is too sensitive in its original form to be shared.

In this blog post, I will tackle some of the most common data privacy questions and how they can change the way you think about managing and protecting your data assets.

FAQ 1: “Is a data privacy tool just for compliance? Does having one mean I have complied with X regulation?”

Don’t rush to get a data privacy tool because you need to comply with personal data protection regulations. Deploying a tool forms part of an approach to compliance but does not ensure full compliance on its own.

You will also need to set up critical data governance and processes, do an inventory of the data assets to be protected and determine which privacy measures need to be applied to meet your requirements.

FAQ 2: “Can we just encrypt everything?

Encryption is just one of the many privacy techniques. Surprisingly, it’s one of the least commonly used. There are many other privacy-enhancing technologies available. For example, format-preserving tokenization provides better data utility, allows you to match the format and length of the data, yet requires less compute and storage, without compromising data privacy.

FAQ 3: “Can data privacy tools allow me to mask the data when it is not in use and unmask it when I want to use it?”

Data privacy tools should not be confused with data security tools or data access tools, which protect the storage of data on disk and control their access.

It may be a surprise, but not all use cases require privacy to be reversible. Even if it is required, reidentification is typically used at the end of data analysis, when there is a need to target a subset of individuals to apply the necessary interventions required by the business.

FAQ 4: “Can data privacy protect me from data breaches?”

Data breaches can still occur when malicious actors gain access to your data, even if it has been de-identified. This is dependent on the controls you have in place when securing access to the data and its distribution. Data privacy helps lower the impact in the event your de-identified data is breached—at least the personal information in the data is protected.

FAQ 5: “Can I delete all my raw data after I have performed de-identification?”

In the lifecycle of your data, there may be a need to create de-identified copies of your raw data for different use cases or different teams.

Having a good data privacy and modern data provisioning solution allows you to apply context-sensitive privacy, while provisioning data. This helps in the creation of de-identified datasets that can be designed specifically for each use case.

Learn how Privitar can help with your organization’s data privacy and provisioning needs—allowing you to expand the universe of data that you can safely analyze.