Clustering: Groups things together to easily recognize similarities and differences in a dataset, which makes it easier to make comparisons
Cohort analysis: Looks at the behavior of a group of people to draw broad insights
Complex event analysis: Provides real-time insight by analyzing event data from various sources and pointing out cause-and-effect relationships. Also known as complex event processing (CEP).
Data mining: Identifies sequences, relationships, and outliers across large datasets, which can be used to assess opportunity and risk
Machine learning: Finds complex patterns and produces accurate predictions that can be used in personalization, fraud detection, and micro-segmentation
Predictive analytics: Predictions about business outcomes based on historical data, statistical modeling, and machine learning
Retention analysis: Used to understand user/customer cohorts, which help determine retention factors and growth strategies