In the first part of the blog series, we discussed how correlation analysis can be leveraged to reduce time to detection (TTD) and time to remediation (TTR) by guiding mitigation efforts early. Further, correlation analysis helps to reduce alert fatigue by filtering out irrelevant anomalies and grouping multiple anomalies stemming from a single incident into one alert. In this part, we throw light on the applicability of correlation analysis in the realm of eCommerce, specifically, promotions.

A North American telecom company struggled for years trying to react quickly enough to new categories and new levels of spam texts and calls. They also did not have a good way to know when and why they would need additional capacity on their own, or any other telecom company’s networks.

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets.

Random forest is one of the most widely used machine learning algorithms in real production settings.