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Databahn Team


DataBahn for Cyber Security Data Orchestration in Snowflake

A lot of enterprises are choosing Snowflake to become its enterprise data lake. Snowflake’s schema flexibility permits the storage of raw data and on-the-fly schema application, ideal for the often-chaotic nature of data lakes. In terms of performance, Snowflake’s architecture excels in querying and analyzing large datasets, facilitating data lake analytics. Robust security features, encompassing role-based access control, encryption, and auditing, ensure data security and regulatory compliance. Data sharing is also straightforward, providing a secure means for collaboration and potential data monetization. With Snowflake’s continued innovation and flexibility to bring in external tables, iceberg tables, Snowflake is becoming the automatic choice for many enterprises, especially because of its unique architecture of separation of storage and compute.

However with Cyber security, though Snowflake is an excellent choice for handling security workloads such as Threat detections, ML powered anomaly detection, Threat Hunting, the challenges of managing custom data pipelines to centralize log ingestion, performance of queries, unpredictable costs have often turned away Security teams from realizing the value of migrating from monolithic SIEMs to data lake powered SIEM like Snowflake.