In an era where sensitive data is a prime target for cyberattacks and compliance violations, effective data classification is the critical first step in safeguarding information. Recognizing the ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...

When it comes to managing data, we need to know where it is – but we also need to know what it is. With the rise in regulatory controls, enterprises now pay more attention to data sovereignty, ...

The study of clustering and classification of uncertain data addresses the challenges posed by imprecise, noisy, or inherently probabilistic measurements common in many modern data acquisition systems ...

An effective data loss prevention (DLP) strategy is essential for protecting your organization's data, but without proper data classification, even the best DLP tools can fall short. Data ...

Information technology and data constitute valuable Connecticut College assets. The purpose of data classification is to identify college data and it’s sensitivity. In order to protect the security, ...

Here's a complete end-to-end demo of what Dr. James McCaffrey of Microsoft Research says is arguably the simplest possible classification technique. The goal of a machine learning classification ...

If you’re a data person, or even if you’re not, you may have heard the statistic cited by Eric Schmidt, executive chairman at Google: “There were 5 exabytes of information created between the dawn of ...

A data storage strategy that addresses data sovereignty builds on the classification of data in the data audit to limit what data can go where. As part of the classification process, data will be ...