Abstract: A method identifies related data visualizations. A computing device displays a data visualization according to a data source. The data visualization displays of one or more first data fields from the data source, and is displayed according to one or more first metadata fields. The device identifies a collection of predefined data visualizations for the data source. For each element in the collection, the device computes a respective ranking according to a plurality of influence scores, each influence score computed according to comparing data fields and metadata fields of the respective predefined data visualization to the one or more first data fields and the one or more associated first metadata fields. The device then selects a subset of the predefined data visualizations that have top ranking and provides an ordered list of the selected subset, including at least one influence score for each included data visualization.

Abstract: Embodiments are directed to managing visualizations of data. Visualizations to monitor may be determined based on metrics associated with the monitored visualizations. Mark values may be sampled from each monitored visualization such that the sampled mark values may be stored with a timestamp. If an amount of the sampled mark values for a monitored visualization exceeds a threshold value mark models may be trained to classify a portion of the sampled mark values associated with the monitored visualization such that the mark models may predict ranges of values for the classified mark values associated with the monitored visualization. If the portion of the classified mark values associated with the monitored visualization has a value outside of the predicted range values, indicating that the monitored visualization may be associated with an anomalous mark value.

Abstract: Embodiments are directed to managing visualizations of data. A visualization associated with one or more community visualizations that are associated with an organization may be displayed. A recommendation score may be generated for each of the community visualizations based on a comparison of meta-data fields. Top ranked community visualizations may be determined based on the recommendation score associated with each of the community visualizations. An influence score may be determined the meta-data fields based on a proportion of a value each meta-data field contributes to the recommendation score of a corresponding top ranked community visualization. A report that includes a rank ordered list of the top ranked community visualizations and the top ranked other meta-data fields may be provided to the user.

Abstract: Embodiments are directed to managing visualizations of data. Visualization models and a user profile may be provided such that the visualization models and the user profile may be associated with an organization. A complexity score for the organization may be provided based on one or more characteristics of the organization. A recommendation model may be provided based on the complexity score and a baseline model. The recommendation model may be employed to determine one or more recommended visualization models based on the user profile such that the recommendation model associates each recommended visualization model with a confidence score. The one or more recommended visualization models may be rank ordered based on each associated confidence score. A report that includes a rank ordered list of the one or more recommended visualization models may be provided to a user associated with the user profile.