This ebook explains how modern cybersecurity teams can leverage data intelligence to detect threats faster, reduce false positives, and scale security operations. It outlines how traditional SIEM tools struggle with cost, schema rigidity, and limited analytics, and introduces a lakehouse-based approach for ingesting, enriching, and analyzing security telemetry. Key use cases include threat detection, historical threat hunting, anomaly detection, and AI-assisted triage. The ebook emphasizes integrating machine learning, real-time analytics, and open architectures to improve visibility across identity, endpoint, cloud, and network data while preserving existing SOC workflows.

Join for free to read