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Security Data Lake ETL and Analytics

Integrate Hunters XDR with your data lake to unify data spread across siloed tools, automatically run advanced analysis on years of log data, and minimize data ownership costs. Hunters XDR acts as both the ETL and the analytics engine on top of your security data lake.

 

 

What is a Security Data Lake?

 

A security data lake is a repository of structured, semi-structured and unstructured security data, consolidating all the security telemetry from an organization in one single source of truth, enabling better decision making.

 

Security data lakes can support analytics at cloud scale and at a fraction of the cost of dedicated SIEM solutions, preparing the organization for the petabyte-scale security challenges already emerging. Data lakes, leveraging the power of cloud computing and scale, have the ability to store virtually unlimited amounts of data in one location, and allow analytics to run on top of the petabytes of stored data. 

 

Why Deploy XDR for Security Data Lake ETL and Analytics?

 

Hunters XDR helps security teams build a security data lake leveraging its built-in ETL capabilities to lift and shift, normalize and organize all the security data. Hunters XDR can pipe into multiple security tools from a wide variety of vendors, and seamlessly ingest all the security data into a unified schema that is digestible and allows to consolidate spread solutions for advanced analytics.

 

Removing the immense heavy-lifting and the challenge of data engineering to prepare security telemetry for easy consumption and analysis can save a tremendous amount of valuable resources, allowing security teams to focus on threat detection and response. 

Hunters’ out-of-the-box analytics and automatic investigations run through the terabytes or petabytes of security data to find threat signals using its unique TTP-based detections as well as native alerts from existing tools. These are automatically enriched with further context, and placed into a massive graph of connected signals and entities.

 

Hunters uses ML models to correlate signals and alerts and dynamically score them, allowing for easy prioritization and quick triage of threats. These insights that the SOC can act upon significantly reduce response time and give security analysts the necessary information and context to respond with confidence.

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Benefits of Deploying Hunters XDR for Security Data Lake ETL and Analytics

  • Unified Data: Having all security data consolidated in one place that allows to run advanced analytics on top of it. Moreover, by unifying the data in the data lake of the organization, enterprises can now address more use cases by looking together at security and non-security data.
  • Detection Coverage: Eliminating the silos of data and unifying detection in one place, to cover the entire attack surface. Having the “hot-storage” data availability enabled by data lakes helps with faster and more accurate detection, eliminating the need to search and query old, siloed data.
  • Easy Investigations: Leveraging Hunters’ automatic investigations, analysts can reduce the time to triage incidents and decide on next steps in a faster and efficacious way.

Hunters XDR + Snowflake Data Lake

Use Hunters’ native integration with Snowflake’s data lake to automatically run analysis on years of log data, minimize data ownership costs, and unify data spread across siloed tools. Hunters XDR acts as both the ETL and the analytics engine on top of Snowflake.