Monitoring the patterns of how data in your organization is treated can help in detection of abnormal data behaviors.
Machine learning can be applied to these patterns to build predictive models that identify potential threats.
When data acts out of character against the predictive models established by the Imanis Data machine learning algorithms, the system can flag possible threats or anomalous data losses for further investigation.
Vice President, Engineering
Senior Analyst, Enterprise Strategy Group
Co-Founder & Chief Analyst
Network Operations Manager
Intelligent threat-sensing backup architecture looks for patterns of data movement and churn, and builds custom predictive models to immediately flag an event as a possible threat or intrusion.
Multiple point-in-time copies of data along with underlying metadata, distributed across geographies, is critical to protecting against data loss. A distributed scale-out architecture allows you to back up petabytes of data quickly, seamlessly, and with ease.
Minimize any impact on business operations and quickly recover after an attack. Quickly and easily locate the objects for recovery using our Google-like catalog, Imanis Data FastFind.