A Fortune 100 Retail Giant Achieved 5x Faster IoT Data Processing Using Real-Time Analytics Platform
Overview
A Fortune 100 retail giant operating thousands of outlets across the United States, renowned for its commitment to food safety, product quality, and exceptional customer experience. It serves customers through a variety of channels, including physical stores, e-commerce platforms, and mobile apps, offering a wide range of products and services.
The retailer struggled to process massive volumes of high-velocity IoT data—over 100K messages per second from cooking and storage equipment—resulting in:
Operational inefficiencies due to delayed insights.
Inaccurate predictive analytics, leading to equipment failures and downtime.
Compliance risks, impacting food safety standards and customer trust.
Solution
Coforge implemented a real-time IoT analytics platform designed for speed, accuracy, and compliance:
Ingested IoT data at scale using 100+ Kafka streams integrated with Spark for ultra-low latency processing.
Applied 50+ business rules for quality checks, asset tagging, and metadata management using Redis Cache, Spark, and MDM tools to boost traceability.
Created 25+ metrics with advanced windowing, thresholding, and moving averages to power 15 real-time dashboards for proactive monitoring.
Leveraged Cassandra for scalable storage and long-term performance analytics.
Deployed AI-driven anomaly detection and predictive ML pipelines to optimize usage, reduce downtime, and maintain food safety compliance.
The Impact
5x faster IoT data processing, enabling instant monitoring of critical equipment.
50% faster operations and 35% improved accuracy in predicting equipment issues.
25% boost in compliance metrics, ensuring better adherence to safety standards and improving customer trust.
