Kliyente: Databricks US
Format: E-book
Laki: 900 KB
Wika: English
Petsa: 30.07.2026
Building a Security Lakehouse
Modernize detection, response and security operations
Traditional SIEM platforms often underperform due to high costs, inflexible schemas and limited scalability. These barriers make it hard to use advanced analytics, keep historical data and integrate machine learning into security operations.
The Databricks security lakehouse provides a flexible, scalable foundation for modernizing security operations. Teams can ingest security telemetry from identity, endpoint, cloud and network sources. Lakehouse architecture enables flexible analysis through its open and governed framework.
Rather than replace existing tools, the Databricks Platform integrates with SIEM, SOAR and case management systems to enhance detection, investigation and automation capabilities.
This blueprint offers a modular reference architecture for building a security lakehouse.
Key steps:
Traditional SIEM platforms often underperform due to high costs, inflexible schemas and limited scalability. These barriers make it hard to use advanced analytics, keep historical data and integrate machine learning into security operations.
The Databricks security lakehouse provides a flexible, scalable foundation for modernizing security operations. Teams can ingest security telemetry from identity, endpoint, cloud and network sources. Lakehouse architecture enables flexible analysis through its open and governed framework.
Rather than replace existing tools, the Databricks Platform integrates with SIEM, SOAR and case management systems to enhance detection, investigation and automation capabilities.
This blueprint offers a modular reference architecture for building a security lakehouse.
Key steps:
- Inventory and prioritize your data sources
- Ingest and normalize security telemetry
- Operationalize detections
- Route alerts and integrate SOC tools
- Support investigation and triage workflows
- Deliver security outcomes
