Articles by SB Team
The Unstructured Data Blindspot: Why Your Most Valuable Assets Are Your Least Protected

When 90% of enterprise data is expected to be unstructured within the next five years, and the NAS market is projected to reach $116 billion by 2032, a dangerous perception gap persists. Many organizations do not view their unstructured data as high-risk or mission-critical, even as it contains their most sensitive information and represents their largest attack surface.

From file systems and NAS platforms to object stores across on-prem and cloud environments, unstructured data continues to grow in scale and complexity. At the same time, ransomware, data exposure, and regulatory pressure are increasing, while security and IT teams struggle with limited visibility and the practical challenges of operating at a petabyte scale.

In this IDC-led discussion, Jennifer Glenn of IDC Research and Jeff Hughes of Rubrik examine why unstructured data has become a persistent blind spot for CIOs and senior IT leaders. The session focuses on market trends, real-world risk patterns, and the operational realities that prevent organizations from effectively assessing and reducing unstructured data risk.

This session will explore:

  • Why unstructured data is often overlooked despite its growing risk and business impact
  • How scale and lack of visibility amplify ransomware and data exposure risk
  • Why do many organizations delay action even when risks are well understood
  • What changes when organizations can see and act on unstructured data at scale

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AI SOC Made Real: Autonomous Cloud Threat Ops at Machine Speed

Attackers log in and move fast. See how Mitiga’s AI-native Cloud Detection & Response feeds Torq’s Autonomous SOC engine to drive closed loop detection, investigation, and remediation across cloud, SaaS, identity, and AI.

Cloud intrusions rarely look like “breaking in.” Attackers are logging in with stolen credentials, abusing SaaS integrations, and moving across cloud and AI infrastructure at machine speed. Meanwhile, SOC teams are drowning in alerts, stitching together fragmented data, and reacting too late to prevent impact.

Now there’s an AI SOC that actually closes the loop.

In this joint session, Mitiga and Torq unveil a real-time, end-to-end AI SOC architecture that detects, investigates, and neutralizes active threats autonomously. Powered by a deep Cloud Security Data Lake.

What you’ll see live

High-fidelity detections with full context: Mitiga’s agentless platform detects attacker behaviors and builds a single attack timeline in seconds to minutes.

Hyperautomation driven by deep forensic data: a Cloud Security Data Lake that retains up to 1,000+ days of normalized log storage – for forensic depth that doesn’t blink.

Closed-loop automation: Mitiga detects and decodes the attack, with alerts that trigger Torq workflows. Torq pulls enrichment and attack context, then orchestrates autonomous response. Together, they eliminate the gap between "alert fired" and "threat contained."

Autonomous case handling at scale: Torq HyperSOC combines a Multi‑Agent System and Hyperautomation engine to triage, investigate, and monitor SOC responses at machine speed.

The manual investigation and response bottleneck just disappeared.

What you'll walk away with

• A practical blueprint for autonomous cloud threat operations built on a Cloud Security Data Lake

• Real-world examples of of how forensic context + automated remediation stop attacks in minutes, not hours.

• Understanding of where human analysts still matter. And where machines should take over

• A path to transforming your SOC into a machine-speed operation that scales with cloud complexity

When attacks move in minutes, your defense needs to move in seconds.

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