Raw telemetry becomes valuable only when it is turned into decisions. The data and analytics layer of the NETNOVA Cloud Platform processes device data in real time and over long periods, so operators can see what is happening now, understand why, and anticipate what will happen next.
Incoming data passes through validation and processing pipelines and is stored in a time-series database designed for high-frequency industrial measurements. Users can explore trends, compare assets and sites, and calculate KPIs such as consumption, availability, efficiency and OEE.
Anomaly detection highlights unusual behavior, including sudden changes, slow drifts and values outside normal patterns, before it turns into a failure. Where historical data is available, we develop machine-learning models for predictive maintenance, demand forecasting and leak or loss detection, tailored to each customer's assets.
Results are delivered through dashboards, scheduled reports, alerts and data exports, or streamed to your business intelligence tools through APIs.