Editorial
The promise of artificial intelligence rests on an increasingly complex foundation: data. While organizations show great excitement about deploying artificial intelligence for efficiency and insight, many are creating significant business risks by treating data privacy as an afterthought. This isn't a sustainable, future-focused approach. As
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Perimeter-first security has become a liability in cloud-heavy, partner-connected enterprises. Breaches are more costly and faster, and each incident underscores the value of data as a business asset under threat. Attackers use valid credentials and living-off-the-land techniques that slip past signature tools. The global average cost of a data
Data center decommissioning is a critical data protection challenge. It goes beyond physical demolition. For many organizations, infrastructure retirement disrupts operations, leading to issues like manual ticket generation and heightened security concerns. Yet with faster hardware refresh cycles, transitioning from legacy systems can become a
Data breaches represent a growing financial threat, with the global average cost per incident exceeding $4.88 million in 2024 . That figure continues to increase as hackers exploit blind spots and employees unintentionally widen them. As data moves through cloud apps, vendor systems, and unmanaged devices, assuming it’s safe in one place creates
Cloud security teams are grappling with a fundamental paradox. While their environments become more dynamic and complex, the tools they rely on often provide a lagging, incomplete picture of risk. Many third-party security platforms depend on public APIs to gather data, creating an inherent delay and a critical visibility gap. This approach is