Snowflake is a data platform that enables users to easily store, manage, analyze, and share high volumes of structured and semi-structured data. Whereas traditional data architectures often consist of multiple databases, data warehouses, and data lakes, Snowflake’s Data Cloud breaks down the barriers between siloed data sources and serves as a single source of truth for a wide range of simultaneous workloads.
The Benefits of Workload Visibility
Improved visibility into the data cloud stack gives users better resource efficiency and optimization of overall spending. Bluesky’s solution for Snowflake visibility synthesizes signals across workloads, infrastructure and usage into a single view that enables customers to rapidly detect and correct performance-related issues. For example, it can alert analysts when a query is inefficient so they can turn int off and create a more efficient one. Bluesky offers even deeper insight into how your Snowflake compute credits are being used across your organization. You can slice and dice the total number of credits your warehouses consume by the user, role and warehouse_name in order to see which teams and team members are running the most expensive workloads.
Get Full Visibility into Snowflake with Bluesky
Bluesky provides crucial insight into every layer of the Snowflake workload so that you can carefully monitor and optimize your usage, whether you’re managing a single account or overseeing Snowflake usage throughout your entire organization.
Bluesky’s SaaS product uses an innovative technology called query patterns to analyze your workloads, then provides actionable recommendations to immediately optimize workloads and predictably stay optimized over time. This gives both data engineers and business leaders unprecedented visibility into data usage so they can focus on deriving business value from data rather than managing it.
With Bluesky You Can:
#1- Optimize Data Cloud cost efficiency and agility
#2 - Reduce Snowflake costs by an average of 37%
#3 - Improve cost per query by an average of 45%
#4 - Save 1000s of hours of work, enabling your data team to focus on creating data-driven business value