Today’s security teams are overwhelmed by a flood of data, pressure to reduce costs, and the need to detect threats quickly. Microsoft’s new Sentinel data lake, now in public preview, offers a unified, cloud-native platform that promises to simplify security data management, break down silos, and deliver AI-ready analytics all without the hassle of managing complex infrastructure.
Unified and Cloud-Native by Design
Microsoft Sentinel data lake is seamlessly integrated into Microsoft Sentinel, leveraging the power of Azure. This fully managed data lake centralizes all security data, empowering organizations to store, analyze, and retain logs and security information in one place.
The platform is tailored for security, helping teams overcome the fragmentation that can slow threat detection and response. With support for multiple analytics methods over a single data copy, it streamlines operations and can reduce storage costs over time.
- Data unification: Easily aggregate logs and asset data from Microsoft services (including M365, Defender, Azure, Entra, Purview, Intune) and more than 350 third-party connectors, such as AWS, GCP, and network devices.
- Efficient retention: Store large volumes of both low-fidelity and critical security logs, optimizing for compliance and forensic needs.
- AI-ready foundation: Centralized, open-format data enables more powerful AI-driven insights and analytics.
Simplified Onboarding and Flexible Integration
Getting started is straightforward. ecurity teams can enable Sentinel data lake with a single click from the Defender portal. The platform works with existing and custom connectors, so organizations can consolidate their data estate and tailor retention to their needs.
- Easy onboarding: Activate directly from the Defender portal, streamlining setup.
- Flexible data routing: Decide how and where to store data, with automatic analytics-tier mirroring into the data lake at no added cost.
- Expanded schema support: Compatibility with current Sentinel table schemas and upcoming industry standards.
Empowering Teams with Advanced Analytics
Sentinel data lake gives analysts advanced querying through Kusto Query Language (KQL) and a new exploration experience for deep historical analysis. Teams can run complex hunting queries, schedule jobs across massive datasets, and promote findings to real-time investigation all from a single interface.
- Open-format analytics: Perform multi-modal analytics on a single data copy, reducing duplication and boosting efficiency.
- VS Code integration: A new extension for Visual Studio Code connects directly to the data lake, supporting Python notebooks and spark/ML libraries for advanced analytics and forensics with no infrastructure setup required.
- Automated jobs: Schedule and automate complex analysis tasks, promoting key insights to active investigations.
Cost-Effective, Flexible Data Management
With Sentinel data lake, organizations gain financial flexibility by decoupling data ingestion and retention costs from analytics. High-volume logs can be inexpensively retained in the data lake tier, while critical data stays in the analytics tier, supporting deep threat hunting and forensic analysis without overspending.
- Cost control: Separate billing for storage and analytics lets organizations optimize budgets and performance.
- Operational flexibility: Example: Send network logs to the data lake, analyze them with scheduled Python notebooks (integrated with threat intelligence), and promote results for active investigation all without new infrastructure.
A New Standard for Security Operations
Microsoft Sentinel data lake changes the game for security teams by making unified, AI-ready analytics accessible and affordable. With streamlined onboarding, advanced analytics tools, and flexible pricing, it empowers organizations to gain deeper insights and respond to threats faster. For teams aiming to modernize their security operations, Sentinel data lake is a compelling solution worth exploring.
Microsoft Sentinel Data Lake: Transforming Security Operations with Unified, AI-Ready Analytics