Abstract: An apparatus, computer-readable medium, and computer-implemented method for visualizing relationships between pairs of columns, comprising identifying a relationship classification corresponding to two columns in a plurality of columns based on a data type of each column in the two columns, applying one or more statistical measures to data in the two columns to generate association data quantifying a plurality of relationships between data values in a first column of the two columns and data values in a second column of the two columns, wherein the one or more statistical measures are determined based at least in part on the relationship classification, and transforming the association data into a visualization, wherein the visualization comprises one or more indicators corresponding to one or more relationships in the plurality of relationships and wherein a layout of the visualization is determined based on the relationship classification.

Abstract: A system and method are disclosed for providing metric recommendations by a cloud event log analytics system. The log analytics system includes a user interface which allows users to view metric recommendations, view, modify, annotate, delete, or create log metrics. In a first embodiment, centroid vectors are created from metadata associated with user access of log metrics. The centroid vectors are compared to metrics vectors created from log metrics and the results are ranked and provided to users as metric recommendations. In a second embodiment, classification rules are inferred for metric matrix tables containing metadata about log metric usage. Classification rules are assigned to a decision tree used to calculate composite probabilities of interest of log metrics. A recommendation matrix incorporate the composite probabilities of interest to predict the degree of interest an analytics user may have in a log metric for a given role.

Abstract: An apparatus, computer-readable medium, and computer-implemented method for visualizing relationships between pairs of columns, comprising identifying a relationship classification corresponding to two columns in a plurality of columns based on a data type of each column in the two columns, applying one or more statistical measures to data in the two columns to generate association data quantifying a plurality of relationships between data values in a first column of the two columns and data values in a second column of the two columns, wherein the one or more statistical measures are determined based at least in part on the relationship classification, and transforming the association data into a visualization, wherein the visualization comprises one or more indicators corresponding to one or more relationships in the plurality of relationships and wherein a layout of the visualization is determined based on the relationship classification.

Abstract: A system and method are disclosed for providing metric recommendations by a cloud event log analytics system. The log analytics system includes a user interface which allows users to view metric recommendations, view, modify, annotate, delete, or create log metrics. In a first embodiment, centroid vectors are created from metadata associated with user access of log metrics. The centroid vectors are compared to metrics vectors created from log metrics and the results are ranked and provided to users as metric recommendations. In a second embodiment, classification rules are inferred for metric matrix tables containing metadata about log metric usage. Classification rules are assigned to a decision tree used to calculate composite probabilities of interest of log metrics. A recommendation matrix incorporate the composite probabilities of interest to predict the degree of interest an analytics user may have in a log metric for a given role.