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See how online businesses can use machine learning to more intelligently support teams as they monitor micro-transaction revenue.

Improving testing efficiency is critical for companies today. Using a fully automated CI/CD process will help get you where you need to go when it comes to automating QA.

The fast-moving digital era has brought created the need for better, more automated revenue monitoring. Companies today can count on AI to monitor revenue streams.

Why? Because monitoring machines and monitoring business KPIs are completely different tasks.

Because opportunities can open and close very quickly on social media, your anomaly detection needs to track and correlate data in real time.

Learn more about the different types of outliers and why knowing these is key for correct outlier analysis.

One of the problems with statistical outliers is that they can be difficult to detect within the context of time series data. In this post, we’ll discuss how we can tune automated detection systems so that they become integral when it comes to identifying outliers across thousands to billions of metrics.