A leading electronics manufacturer successfully reduced data collection and loading costs by 90% and increased production yield from 50% to 90% by consolidating disparate data silos and implementing SQream’s GPU-accelerated analytics platform for scalable anomaly detection. Facing complex and fragmented data infrastructure, the manufacturer centralized data and established an end-to-end AI platform. Utilizing SQream’s ability to ingest and analyze multi-petabyte-scale sensor and machine data across thousands of tables, the system applied AI-driven anomaly detection algorithms to identify faults and defects early in the production process, enabling timely machine maintenance and optimization on the production floor.

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