This paper outlines best practices for ingesting and normalizing security logs in Snowflake. It details options like Snowpipe for near-real-time ingestion, COPY INTO for batch loads, and Snowpipe Streaming for low-latency streaming. Secure data sharing eliminates ETL by providing live read-only access to shared data. Snowflake connectors for Spark, ServiceNow, and Kafka simplify integration. For normalization, storing raw data is recommended, with transformations handled via views or dynamic tables. Schema detection and evolution help manage semi-structured data. Standards like OCSF, ECS, and CIM can guide consistent formatting, supporting efficient analytics and threat detection.

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