Abstract: Systems and methods create and modify augmented deal structure using specialized components working together in a technical system by aggregating and transforming inputs. Big Data issues are controlled and restriction rules along with specialized components work together to synthesize an augmented deal structure. This augmented structure is presented through a graphical user interface configured to provide at least one of an interactive analysis (providing sensitivity analytics) and a batch processing capability.

Abstract: This disclosure describes techniques that include predicting a business metric associated with a given business enterprise using machine learning algorithms that have been trained on data, from other businesses, about that same business metric. In one example, this disclosure describes a method that includes selecting, from a data set, a training data subset and a test data subset; generating a plurality of candidate models configured to generate a predicted output metric, wherein the plurality of candidate models is generated by applying a plurality of machine learning algorithms to the training data subset; evaluating, using the test data subset, each of the plurality of candidate models to select a chosen model; receiving production data that includes data representing input metrics for a business entity not included within the plurality of business entities; and generating a predicted output metric for the business entity.