Case Study: a Fortune 500 subsidiary improves fleet efficiency with NeenOpal's Snowflake and Power BI solution

Fortune 500 Subsidiary - Customer Case Study

The client, a Fortune 500 subsidiary, was unable to gain insights from the vast and unsynchronized sensor data collected by its garbage truck fleet. Facing challenges with data complexity and inconsistencies, the company engaged NeenOpal to help improve fleet performance, reduce fuel use, and enable preventive maintenance using Snowflake and Power BI.

NeenOpal implemented a solution to synchronize the sensor data and built interactive Power BI dashboards for analysis. They deployed machine learning for anomaly detection and created custom algorithms to track fuel consumption. As a result of NeenOpal's work, the client achieved a 15% increase in fleet management efficiency, a 10% reduction in fuel usage, and detected potential maintenance issues 75% faster.