Abstract: The DATA LEARNING AND ANALYTICS APPARATUSES, METHODS AND SYSTEMS (“DLA”) provides a data learning platform that analyzes and incorporates data knowledge from new data event updates (e.g., in a real-time stream, in a batch, etc.). In one implementation, the DLA provides a real-time data mining mechanism that accommodates an ever increasing data load instantaneously with reduced complexity, e.g., without re-building the data analytical model in its entirety whenever new data is received. In this way, the DLA provides an incremental learning mechanism for data analytics and thus the latency for real-time data assessment is reduced and the data processing efficiency is improved.

Abstract: A computer system, method and computer program product for enabling data analysis is provided. An analytical engine, executable on a computer, provides a plurality of knowledge elements from one or more data sources. The analytical engine is linked to a data management system for accessing and processing the knowledge elements. The knowledge elements include a plurality of records and/or variables. The analytical engine updates the knowledge element dynamically. The analytical engine defines one or more knowledge entity, each knowledge entity including at least one knowledge element. The knowledge entity, as defined by the analytical engine, consists of a data matrix having a row and a column for each variable, and the knowledge entity accumulates sets of combinations of knowledge elements for each variable in the intersection of the corresponding row and column.