Antoine Trad, IBISTM, France

The Applied Polymathical/Holistic Mathematical Model for Integrating Data Sciences (AHMM4IDS) supports Enterprise's transformation projects (simply Project). The AHMM4IDS uses various Mathematical Models (MM), that abstract, incorporate, and integrate Data Sciences (DS), AI-Subdomains, Information Communication System (ICS) components with Project's transformed resources. Transformed resources can be services (and artefacts), success factors (or calibration variables), business processes (and scenarios), mixed-methods, AI-Models, and adequate Enterprise Architecture (EA) Models (EAM). MMs, mixed-methods' based services, artefacts, and EAMs can be used to establish set of DS Patterns (DSP) that include DS technics/capabilities, data-platforms' access (and management), algorithms-functions, mapping concepts, unbundled services; to model and implement Decision Making Processes' (DMP) related infrastructure, data-storage(s), components-models, and end-users' integration. The integration of DSPs enforces and automated DMPs, Project's validity-checking, and Gap Analysis (GAPA); which all need adapted interfaces to access Enterprise, Project, Data-storage(s), ICS, EAMs, pool(s) of Artificial Intelligence (AI) services, and other types of resources. On the other hand, DSPs communicate with other, by using Project's and AI components; and can use also various medias-types formats, like the eXtensible Markup Language (XML) format, and many others. Imported (or exported) DSs' contents and structures are combined with other Project's artefacts and components, to deliver DSPs for various AI-Subdomains.

Data Sciences, AI-Subdomains, Polymathical mathematical models, Business and common transformation projects, Enterprise architecture, Artificial intelligence, Qualitative and quantitative research, and Critical success factors/areas.