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For example, what should the priority be—quick recovery and return to operations, forensics to determine the cause of the attack, or minimizing data loss during recovery?

If a quick recovery is prioritized, then organizations are generally sacrificing the ability to perform forensics to determine how the attack occurred and propagated, which opens the door to a repeat attack.

Similarly, determining exactly what data is impacted as part of the attack can also take time for administrators to pour through logs to assess the situation.

For example, a programmer might need to create an algorithm to analyze a batch of pictures and determine if a dog was in the picture.

The ML system then can set off on its analysis quest to find pictures that contain dogs while also continuing to refine and tune (or learn) its understanding.

The Rubrik Zero Trust Data Management™ platform can then feed that information into a machine learning pipeline that forms intelligent insights that streamline the ransomware recovery decision-making process.

These snapshots are being taken via the on-premises Rubrik Cloud Data Management (CDM) platform.

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