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WEBINAR

WEBINAR

WEBINAR

Detection and Investigation with the Security Data Lake

Detection and Investigation with the Security Data Lake

OS

Omer Singer

RL

Russell Leighton

Threat detection in the cloud requires a combination of visibility and context. But in order to gain actionable insights from your data, it needs to be centralized, normalized, and structured in a way that supports high-scale analysis and investigation.

Cloud data platforms like Snowflake offer a scalable foundation for storing petabytes of business and security data for long-term retention. By introducing a purpose built security analytics platform like Panther, security teams can operationalize their data lake to correlate activity across applications and infrastructure, detect signs of breach, and trigger high-fidelity alerts to third-party applications like Slack, PagerDuty, and Jira.

Join Snowflake’s Head of CyberSecurity, Omer Singer, and Panther Labs Principal Engineer, Russell Leighton, discuss how you can use Panther and Snowflake to:

  • Gain new security visibility with detections-as-code and a central security data lake

  • Detect and alert upon anomalies by regularly baselining user behavior

  • Correlate suspicious activity with normalized security data and scheduled alerts

  • Validate security controls automatically with code-driven compliance policies

  • Identify compromised accounts and insider threats in your Snowflake  

We missed you at the live session

But you can still catch up — watch the full recording to learn why traditional detection methods fail and how Panther solves them.

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