Autonomous Data Cloud for AI-driven analysis.
Cyber Attacks pose significant risk to today’s enterprises, and growing trends like IoT and edge computing are increasing vulnerabilities. To help mitigate tasks, SecOps teams are charged with analyzing billions of events to find patterns and anomalies that suggest malicious intent.
Regardless of the depth of analysis required, the sheer volume of incidents generated is more than humans can without automation. Security operations is a prime use case for AI and Machine Learning, but diverse data sources, data lakes and platforms often stand in the way. Accessing and investigating data across these silos requires significant technical expertise, query language mastery and platform specific certifications. All of these obstacles result in teams that are understaffed leveraging technology that is underutilized - all of which increases security risk to an organization.
Gemini allows Security Operations teams to do more with less. Through Gemini Enterprise, all enterprise data is unified so that analysis can be done across data silos. Instead of needing to learn the platform specific query languages, queries can be run across everything through simple ANSI SQL. With that level of data availability, teams are able to implement AI and ML by leveraging open source tools such as TensorFlow.
By utilizing the latest AI techniques, Security Operations teams can finally get ahead of the noise and drive actionable intelligence. Instead of reactively responding to security incidents, teams can proactively analyze and prevent risk areas while tying everything back to business outcomes.
Gemini’s single unified query gives the power of converging massive amounts of critical data for full contextualized analysis at scale. This level of data availability gives security operations teams the visibility and tools they need to mitigate and prevent security risks from affecting their business.
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