Toptal helps global food and beverage company cut SQL query execution time by 75%.
A global food and beverage company struggling with slow data models partnered with Toptal to accelerate access to product and inventory insights through SQL optimization and standardized dbt models.
Client
A global food and beverage company producing snacks and drinks sold across international markets.
Employees
Revenue
Industry
Consumer Packaged GoodsDelivered Services
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Schedule a CallChallenge
Slow data models in Snowflake were affecting analytics workflows, with some dashboards failing to load altogether, making it difficult to quickly identify product gaps across stores, assess inventory needs, and compare competitor availability.
Solution
Optimized SQL Queries
Toptal analyzed and tuned SQL queries running on Snowflake, addressing performance bottlenecks that were slowing the company’s data models and analytics workflows.
Standardized dbt Models
Building on the existing Snowflake environment, the data engineering work introduced standardized dbt models to create more consistent and efficient workflows for product and inventory analysis.
Outcome
75% Faster Queries
The optimized SQL queries reduced execution time by 75%, allowing dashboards that previously struggled to load to return product and inventory data in seconds.
Better Inventory Decisions
Faster, more dependable analytics helped the company identify product gaps across stores, determine inventory distribution needs, and compare product availability with competitors.
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