Industrial IoT

How Industrial IoT is Influenced by Cognitive Anomaly Detection and Prediction

On-demand Webinar

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:

  • An introduction to anomaly detection and prediction for Industrial IoT, and why this is an important opportunity for businesses to take advantage of now
  • The evolving landscape of Industrial IoT, and how Machine Learning is augmenting cognitive anomaly detection
  • Challenges in the market and why technologies are aligning to suit business needs
  • Traditional approaches to anomaly detection vs. cognitive anomaly detection, and the steps involved in the process
  • Use cases and demonstrations in real world scenarios

About DataRPM

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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