The Industrial IoT sector is facing maintenance challenges related to their data processes. Traditional methods of anomaly detection aren’t providing the right solutions for every entity, which is why Cognitive Anomaly detection is filling the gaps in predictive maintenance.
Progress DataRPM has developed an innovative, effective new route of anomaly detection and prediction in Industrial IoT. A Machine Learning and Data-First solution is providing prevention and optimization for organizations while simultaneously driving data value and enhanced customer experiences.
View this on-demand webinar where Ronald van Loon, ranked number 3 influencer in the world for Big Data and IIOT & Taj Darra, Data Scientist at Progress DataRPM as they discuss:
Anomaly Detection and Prediction powered by Progress® DataRPM™ automates data science, enabling asset-intensive organizations to gain exceptional control over the torrent of sensor data coming from every machine. The automated, patented solution detects and predicts anomalies, delivers machine health insights, reduces the time required to develop and operationalize models, and helps data scientists be more effective.
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