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Snowflake Warehouse Management with ROI in Mind

If you’re new to Snowflake, you might be confused by the term “Warehouse”. Don’t let it fool you, because in Snowflake’s context, Warehouse refers to virtual compute resources rather than a physical storage place. Snowflake Warehouse management for small BI and analytics teams is fairly straight forward if you start off on the right foot.

A majority of Snowflake’s cost is based on warehouse (compute) utilization. Therefore, it’s crucial to be thoughtful about how you design and deploy your Warehouses to optimize your usage and minimize your cost.

Segmentation of Warehouses

One of the key factors in optimizing your Snowflake Warehouse is segmentation by use case and spend categorization. For instance, our Snowflake instance currently consists of 5 warehouses, with each one serving a specific purpose. We started with X-Small or Small instances that can process thousands up to tens of millions of records, and gradually scaled up as needed.

However, over-segmenting and creating too many warehouses is not recommended. This can lead to unnecessary concurrent warehouse instances and significantly increase your spend. Additionally, detailed spend tracking can become very expensive and difficult to manage. Therefore, it’s important to strike a balance between segmentation and cost optimization to achieve the best outcome for your Snowflake usage.

Warehouse Segments and Lessons Learned…

Read more on our Medium Blog

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Ryan Goodman Founder
Ryan Goodman has been in the business of data and analytics for 20 years as a practitioner, executive, and technology entrepreneur. Ryan recently created DataTools Pro after 4 years working in small business lending as VP of Analytics and BI. There he implanted an analytics strategy and competency center for modern data stack, data sciences and governance. From his recent experiences as a customer and now running DataTools Pro full time, Ryan writes regularly for Salesforce Ben and PactBub on the topics of Salesforce, Snowflake, analytics and AI.