Toptal enhances data efficiency and cuts operational costs by 30% for global food company.

A Fortune 500 food and beverage company sought to optimize its data management, reduce costs, and improve SQL processes on its Snowflake platform.

Client

A leading global food and beverage company with a portfolio of iconic brands spanning snacks, drinks, and nutrition products.

Employees

100,000+

Revenue

$92B

Industry

Consumer Products

Delivered Services

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Challenge

The global company faced inefficiencies in SQL optimization and data verification, resulting in increased costs and operational delays on its Snowflake platform.

Solution

Targeted SQL Optimization

Toptal improved SQL queries and adjusted Airflow scheduling, tackling inefficiencies and streamlining data management.

Snowflake Architecture Adjustments

By implementing DBT for data modeling and refining the Snowflake data architecture, Toptal enhanced system performance and positioned the company for future scalability.

Outcome

Significant Cost Reduction

The optimizations led to a 30% reduction in operational costs on the Snowflake platform, allowing for better resource allocation.

Improved Data Efficiency

Toptal’s improvements resulted in more efficient data management and availability, enhancing the company’s overall operational effectiveness.

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