Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling. These platforms support the independent use and collaboration among data scientists and their business and IT counterparts, with automation and AI assistance through all stages of the data science life cycle, including business understanding, data access and preparation, model creation and sharing of insights. They also support engineering workflows, including the creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances or as a fully managed cloud offering.
Decision intelligence platforms (DIPs) are software used to create solutions that support, automate and augment decision making of humans or machines, powered by the composition of data, analytics, knowledge and artificial intelligence (AI) techniques. DIPs must have collaborative capabilities for decision modeling, execution and monitoring. DIPs are used to design decision-centric solutions, explicitly model decisions, orchestrate decision execution flows, and evaluate and govern decisions and audit their outcomes. Optional features include logic-based techniques, machine learning, business intelligence, natural language processing, optimization, graph technology, AI agents, simulation, real-time event stream processing and multi-structured data preparation.