The Data and Privacy Blog

From Data Loss to Data Movement For many years, the term Data Loss Prevention (DLP) has been the standard way to describe technologies that protect sensitive information. Banks deployed it to prevent customer data from leaving the network. Healthcare organizations relied on it to detect patient records in email. Enterprises used it to monitor endpoints and block confidential files from being copied to external devices. DLP solved a real problem for the architecture of its ti

From Data Loss to Data Movement For many years, the term Data Loss Prevention (DLP) has been the standard way to describe technologies that protect sensitive information. Banks deployed it to prevent customer data from leaving the network. Healthcare organizations relied on it to detect patient records in email. Enterprises used it to monitor endpoints and block confidential files from being copied to external devices. DLP solved a real problem for the architecture of its ti

Compliance was designed for a world where data stayed put. Clear system boundaries. Predictable flows. Centralized control. In that world, compliance could be enforced through restriction, periodic audits, and after-the-fact remediation. That world no longer exists. Today, sensitive data moves continuously across SaaS tools, cloud platforms, partners, and AI systems. In this reality, compliance cannot be treated as a static checklist or a retrospective exercise. It must opera

Data Must Move to create value — But Movement Creates Risk Data must move to create value — yet movement creates risk. This tension sits at the center of modern enterprise security and compliance. Organizations depend on data flowing across systems, teams, partners, and AI platforms to operate and innovate. At the same time, every transfer increases exposure, regulatory risk, and loss of control. The challenge facing enterprises today isn’t how to stop data from moving. It’s