One of the world’s leading bed banks – a wholesaler of hotel allocations to B2B and B2C clients – recently experienced a surge in bookings. Great news, right? Not really.

A glitch caused room prices from one of their hotel suppliers to drop from $100+ per night to JUST $8. Imagine how much this glitch could have cost them if left unchecked.


Hotel glitch


Fortunately, Anodot caught the anomalous spike early and correlated it to a simultaneous event – an API error from one of their hotel suppliers.

This type of anomaly is a perfect example of how critical data correlation is to anomaly detection and root cause analysis.

WATCH THIS VIDEO by Anodot Data Scientist Inbal Tadeski at the Strata Data Conference to learn more about the importance of identifying relationships between time series metrics in forecasting, root cause analysis, and more.

Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

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