Facilitating efficient identification of relevant data

A computer-implemented method comprising:

• identifying a set of candidate metrics for which to determine relevance to a user;
• determining a set of distribution parameters for each candidate metric, each set of distribution parameters including a first distribution parameter based on implicit positive feedback associated with the metric, wherein determining the set of distribution parameters for each candidate metric includes determining the first distribution parameter based further on usage data associated with the metric and determining a second distribution parameter using the usage data associated with the metric and direct implicit negative feedback obtained in accordance with the user not selecting or clicking on data associated with a candidate metric from the set of candidate metrics and, wherein the candidate metric is selected from the set of candidate metrics measuring various performance data associated with an organization and is selected based on an occurrence of an anomaly associated with the metric;
• generating a distribution for each candidate metric using the corresponding set of distribution parameters;
• sampling each distribution to identify a relevance score for each candidate metric indicating an extent of relevance of the corresponding metric to the user, wherein the relevance score indicates the metric is relevant to the user based on the relevance score being in a set of highest relevance scores among a set of relevance scores or based on the relevance score exceeding a threshold relevance value;
• and
• based on the relevance scores for each candidate metric, designating at least one candidate metric of the set of candidate metrics as relevant to the user.

A computing system comprising:

• a processor;
• and
• computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, configure the computing system to:
• means for determining a set of distribution parameters for a metric, wherein a first distribution parameter is determined based on implicit positive feedback obtained in relation to the metric and usage data associated with the metric and a second distribution parameter is determined based on the usage data associated with the metric, wherein the second distribution parameter is determined using the usage data associated with the metric and direct implicit negative feedback obtained in accordance with the user not selecting or clicking on data associated with a metric from a set of metrics and wherein the metric is selected from the set of metrics measuring various performance data associated with an organization and is selected based on an occurrence of an anomaly associated with the metric;
• means for generating a distribution for the metric using the set of distribution parameters for the metric;
• and
• means for identifying a relevance score of the metric using the distribution, the relevance score indicating an extent of relevance of the metric to a user, wherein the relevance score indicates the metric is relevant to the user based on the relevance score being in a set of highest relevance scores among a set of reference scores or based on the relevance score exceeding a threshold relevance value.