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How to operationalise time-series analytics
In enterprise IoT, more and more business critical automation use cases depend on the analysis of historical data samples. Typical use cases involve real-time or near real-time anomaly detection and forecasting for predictive or preventive maintenance and SLA adherence.

In recent years, a wealth of new analytics algorithms have become accessible to everyone. The business challenge is now shifting from offline data exploration and analysis towards efficiently operationalising IoT analytics to generate sustainable business benefits.

In this webinar, we use real-life use cases to show you how to address the challenges of coupling the math behind the analytics formulas with the right business context.

We will also demonstrate how Waylay’s Time Series Analytics Module addresses the 4 main pillars of AI-powered automation rules in IoT: explainability, adaptability, operability and scalability.
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