Selector’s software-as-a-service employs machine learning and NLP-driven, self-serve analytics to provide instant access to actionable insights and reduce MTTR by up to 90%. Selector Analytics uses artificial intelligence and machine learning to conduct three essential functions and provide actionable insights to network, cloud, and application operators. Selector Analytics collects any data (including configurations, alerts, metrics, events, and logs), from various heterogeneous data sources. For example, Selector Analytics may harvest data from router logs, device or network metrics, or device configurations. Once collected, Selector Analytics normalizes, filters, clusters, and correlates metrics, events, and alarms using pre-built workflows to draw actionable insights. Selector Analytics then uses machine learning-based data analytics to compare metrics and events and conduct automated anomaly detection.