1. A computerized method for predicting one or more desired properties of external nodes based on a selected group of nodes about which it is known whether the nodes have the one or more desired properties, wherein the one or more desired properties are not known with respect to the one or more external node because the one or more external nodes lack a relationship with a given entity, the method comprising: storing in one or more data structures a first data set regarding external nodes and a second data set regarding nodes in a selected group, each data set having one or more data items representing one or more events relating to or attributes of each node in the data set, the second data set including one or more types of data items not included in the first data set; virtualizing the second data set regarding nodes into a modeled second data set after the first data set regarding external nodes at least by eliminating from the second data set the one or more data item types not included in the first data set; modeling the virtualized second data set to identify from the modeled second data one or more modeled events or attributes of nodes in the selected group that are statistically likely to identify the nodes that have the desired properties; and predicting which of the external nodes are statistically likely to have the one or more desired properties based on the identified plurality of modeled events or attributes and the events or attributes in the first data set.