Ranking anomalies associated with populations of users based on relevance

A method comprising:

• storing in a database, a plurality of records of a plurality of entities, each record storing one or more attributes describing an entity of the plurality of entities;
• performing data collection, the collected data representing responses associated with the plurality of entities;
• identifying a set of anomalies based on the collected data, wherein each anomaly in the set of anomalies is associated with a set of users representing a population;
• for each anomaly in the set of anomalies, determining a relevance score for the anomaly;
• ranking the set of anomalies based on the relevance scores, wherein ranking the set of anomalies comprises:
• determining that a first anomaly is associated with a first population that corresponds to a pre-defined team;
• determining that a second anomaly is associated with a second population that does not correspond to any pre-defined team;
• ranking the first anomaly higher than the second anomaly at least based in part on the first population corresponding to the pre-define team and the second population not corresponding to any pre-defined team;
• determining a subset of anomalies based on the ranking;
• and
• sending one or more alerts based on the subset of anomalies.

A non-transitory computer-readable storage medium storing instructions which, when executed by one or more processors, cause:

• storing, in a database, a plurality of records of a plurality of entities, each record storing one or more attributes describing an entity of the plurality of entities;
• performing data collection, the collected data representing responses associated with the plurality of entities;
• identifying a set of anomalies based on the collected data, wherein each anomaly in the set of anomalies is associated with multiple entities comprising a subset of the plurality of entities;
• for each anomaly in the set of anomalies, determining a relevance score for said each anomaly based on factors comprising information describing the subset of entities associated with said each anomaly, wherein the factors used for determining the relevance score for said each anomaly comprise a number of entities in the subset of entities associated with said each anomaly;
• ranking the set of anomalies based on the relevance score for each anomaly in the set of anomalies;
• determining a subset of the set of anomalies based on the ranking;
• and
• sending one or more alerts based on the subset of anomalies.