10 Tips for Better Security Data Management

This article provides best-practice guidance for security telemetry and data management, advising organizations to standardize log schemas, prioritize normalization and correlation, vet AI/LLM training data lineage, evaluate data sources by cost and value, suppress low-fidelity "garbage" data, build custom detection content, cross-pollinate SecOps with data science expertise, decouple analytics for flexibility, and consider security data lakes to improve observability and reduce operational costs.