How Personio drove cost awareness while scaling Snowflake across 280+ users
- 60%
- reduction in dbt pipeline execution times
- 280+
- direct Snowflake users supported
ClickUp operated Snowflake as their central source of truth supporting hundreds of users across multiple teams. They built homegrown cost monitoring using open-source dbt packages and custom Hex dashboards, which became time-intensive to maintain as scale increased. The team wanted granular visibility down to the dbt model level without dedicating engineering resources to building and maintaining internal dashboards.
SELECT provided comprehensive cost visibility that ClickUp's homegrown solution aimed to achieve, with quick and straightforward setup. The platform's automated insights eliminated manual legwork of cost analysis while enabling granular monitoring down to individual dbt models. Weekly Slack digests created a macro-to-micro approach for efficient, ongoing cost management.
One of the most helpful cost rituals we've setup from SELECT is the weekly spend digest sent to Slack. I can start high level and ensure things are in check. If not, I can very quickly drill down into specific workloads which may have driven the cost spike and remediate them before they become a bigger issue.
Michael Revelo, Manager of data and analytics engineering at ClickUp
ClickUp operates a modern data stack with Snowflake serving as the definitive source of truth across the company. The platform supports hundreds of users including data engineers, analysts, and business stakeholders who are able to run direct queries after completing ClickUp's homegrown SQL training course. Beyond direct query access, Snowflake powers ClickUp's entire operational ecosystem. Census enables reverse ETL to push data from Snowflake to power marketing campaigns, RevOps workflows, and sales operations across tools like Salesforce, Pocus, and various ESP platforms. This warehouse-first approach means that changes made in Snowflake propagate throughout ClickUp's entire operational infrastructure, making cost management and optimization critical for both data platform stability and business operations.
Before SELECT, ClickUp built internal cost monitoring using open-source dbt monitoring packages. Using this metadata, the team built custom cost monitoring dashboards in Tableau and later Hex. While the homegrown solution provided basic visibility, it became increasingly difficult to maintain as ClickUp's Snowflake usage scaled. The team recognized they needed a more sustainable approach that wouldn't require ongoing engineering investment.
ClickUp's adoption of SELECT was driven by a proactive cost management philosophy rather than reactive cost problems. Michael recognized the importance of establishing proper cost monitoring infrastructure before issues emerged. This forward-thinking approach aimed to prevent the common scenario where finance suddenly demands cost cuts for critical infrastructure that teams can't afford to eliminate.
SELECT transformed ClickUp's cost management approach through automated weekly Slack digests that provide high-level cost trending with the ability to drill down when needed. This systematic approach prevents wasted time on micro-optimizations while ensuring no significant cost increases go unnoticed. When alerts indicate cost growth, the team can quickly identify whether issues stem from warehouse optimization needs, user behavior, or dbt model inefficiencies.
SELECT's visibility immediately surfaced several cost optimization opportunities that ClickUp's homegrown solution had missed. One major discovery involved Census configurations where marketing teams had set up live syncs for audiences despite ClickUp's batch data processing. The team also identified users forgetting to switch back from larger warehouses after ad hoc analysis work and opportunities for warehouse consolidation across tools with similar usage patterns. Additional optimizations included incrementalizing expensive dbt models and switching table types from permanent to transient for appropriate use cases.
Perhaps the most significant cultural change was embedding cost considerations into every data project and decision. SELECT's visibility created a culture where team members proactively think about how their actions impact costs and feel accountable for their Snowflake usage. As ClickUp prepares for major infrastructure changes including real-time data ingestion, Iceberg adoption, and team expansion, SELECT will serve as the foundation for managing cost growth alongside business growth.
Explore how SELECT helps teams reduce warehouse waste, improve visibility, and act on data cost insights.
“SELECT is a team favorite - its cost monitoring and auto savings give us peace of mind that our Snowflake spend is in check. The platform’s detailed insights across SQL queries, dbt, and Looker usage provides a comprehensive view into credit spend that is unmatched by other solutions. SELECT has helped us significantly optimize how we use Snowflake.”

“SELECT's app has become an invaluable resource to our company. It clearly breaks down our costs to allow us to focus on the most important areas of cost. SELECT has repeatedly surfaced inefficient common query patterns, and has helped us spot 200 TiB of unused tables to drop, resulting in continued significant cost savings. SELECT is always adding new features to help their customers better understand and reduce their spending. We can't recommend them highly enough!”

“I love clicking through SELECT to understand how our environment and workloads are evolving. I probably check it every day. It's coffee and SELECT for me every morning.”

“SELECT helps us quickly identify inefficient queries that consume unnecessary Snowflake credits, providing all the information we need in a single application. With the Automated Savings feature, we were able to allocate credits to new compute-intensive data projects.”

“This is the easiest thing we've ever done to save money - 20x ROI. Does this not exist for AWS?”

“SELECT provides our team with complete visibility into all aspects of our Snowflake bill and usage. Our team regularly uses SELECT to monitor costs and get alerted on key changes. The dbt & Looker integrations are also super helpful for identifying performance bottlenecks.”

“SELECT helped us monitor and reduce our overall Snowflake spend by almost 40%. The reporting showed me bottlenecks in minutes that would’ve otherwise taken weeks to dig through metadata and sort out. The 'Automated Savings' savings feature alone is saving us over $10k a month across our accounts, allowing us to bring on new workloads.”

“Before SELECT, we were blind to our Snowflake cost drivers. Minutes after install, we identified a single job that was driving over 20% of our costs. The instant visibility & not having to build & maintain our own monitoring makes a big difference for a lean team like ours.”
