Progress DataRPM AWS-based anomaly detection

Progress Software has announced the availability of the Progress DataRPM self-service anomaly detection and prediction option for the Industrial Internet of Things (IIoT) market. It is designed to empower R&D and innovation groups with better decision-making capabilities for IIoT proof-of-concept (POC) and pilot execution.

Hosted on Amazon Web Services (AWS), AWS will also offer free trials of Progress DataRPM cloud instances for qualified manufacturers with connected sensors and the ensuing time series data. The trial will allow companies to load their data securely on AWS, detect equipment anomalies, predict failures before they occur and validate against failures — both known and unknown — thereby confirming proactive steps that should be taken in advance to avoid unplanned downtime and unscheduled maintenance.

Through the Progress DataRPM anomaly detection and prediction option, industrial decision-makers, data scientists, heads of innovation, R&D and machine learning and big data decision-makers now have access to self-service through the end-to-end automation of the steps from data ingestion and analysis to insights visualisation. Users can easily upload sensor data, map the attributes and click ‘run’. The entire cognitive flow works in a fully automated fashion to show near-immediate results. Results are shown in ‘stories’, in a human-readable format that highlights patterns and anti-patterns in the sensor data. Using drill-down and filters, users can gain a better understanding of the behaviour of assets and most important sensors for predicting the most likely failures states.