Correlating parallelized data from disparate data sources to aggregate graph data portions to predictively identify entity data

A system comprising:

• a data store configured to receive streams of data via a network into an application computing platform;
• and
• a processor configured to execute instructions to implement an application configured to:
• receive data from multiple data sources at a computing system including one or more processors and memory configured to process the data in parallel to form parallelized data, the parallelized data being further converted by a format converter to graph-based data from one or more of the multiple data sources;
• classify data representing a subset of the parallelized data to identify a class of observation data;
• identify data representing one or more entity attributes associated with the observation data;
• construct one or more content graphs in a graph data format based on the class of observation data and the one or more entity attributes;
• correlate the subset of the parallelized data to other subsets of the parallelized data associated with the class of observation data to form correlated subsets of the parallelized data;
• aggregate data representing individual entities to form a set of entities based on the correlated subsets of the parallelized data;
• and
• modify a graph data arrangement to enrich data stored in association thereof.