Snowflake’s mission is to mobilize the world’s data. For that, they deliver the Data Cloud, a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance.
Snowflake, like most organizations, uses multiple solutions from various vendors like Azure, Google Cloud, and several SaaS applications, as well as security products for endpoint, cloud, network, etc. While this allows them to select best-of-breed security products, making sense out of the data is a challenging process due to the lack of thorough analytics and cross-surface correlation that traditional monitoring and reporting tools provide. As a result, detection and response is a slow, siloed and complex process, leading to breaches left undetected and attacks manifesting themselves in production.
- Speeding up time to detect threats.
- Reducing triage time so it would take minutes instead of hours or days.
- Upscaling analysts’ daily tasks from their 10 people team so they could focus only on real attacks.
- Lack of business agility due to the long detection and triage time resulting from siloed detection and monitoring tools
- Analysts suffering from false-positive burnout due to the level of noise in the SOC without context or explanation
- Wasting human resources on manual investigations that could be automated
- Difficulty to hire and retain security people with vast experience and knowledge
Snowflake’s platform is the engine that powers and provides access to the Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Snowflake’s customers have more than 250PB of data managed by them.