Delayed business insights cost companies millions of dollars with data-centric companies, such as web-based businesses, adtech, fintech and IoT, facing particularly unique challenges. It is impossible to manually track the millions of metrics that are generated in today’s digital businesses and businesses are increasingly finding that static thresholds for seasonal data are either meaningless or cause alert-storms. Companies are often finding that dashboards can’t keep up with these sudden spikes and the data can only ever be used in hindsight.

In this webinar Uri Maoz, Vice President of US Business, discusses how predictive anomaly detection can better identify revenue-impacting business incidents in minutes, not days or weeks. He also covers the benefits and challenges of implementing anomaly detection, sharing industry benchmarks and customer case studies. Uri has spoken at numerous events and conferences about Anomaly Detection.

In this Webinar, Uri covers:

  • The fundamentals of Anomaly Detection, what it means and how you can get real-time business incident detection using Anomaly Detection
  • The steps one should take to implement a real-time Anomaly Detection solution in scale
  • The various business use cases from customer experience and how Anomaly Detection helped them save millions of dollars


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Written by Anodot

Anodot is the Autonomous Analytics company. We use an advanced AI platform to detect, correlate and forecast anomalies in real time, helping businesses find and fix issues faster than is humanly possible.