Method and system for developing and deploying data science transformations from a development computing environment into a production computing environment

Abstract

A method and system facilitates the development of data science transformations in one programming language and the deployment of the data science transformations in another programming language, according to one embodiment. The method and system preserves relationships, functions, configurations, and characteristics between combinations of data transformations, according to one embodiment. The preservation of the relationships, functions, configurations, and characteristics is enabled by developing and providing a set of low-level (e.g., atomic) transformations that enable users to build their own models, libraries, and configurations into macro-transformations (e.g., conglomerate transformations), according to one embodiment. Deploying the data science transformations into production computing environments is useful for providing or supporting a number of types of software services, such as, predicting user behavior, customizing user experiences, supporting marketing initiatives, providing empirically-backed recommendations, predicting user preferences for software interactions, and/or otherwise exposing patterns that are identified from historical and transactional data, according to one embodiment.