Enterprise Transformation Projects-Cloud based Artificial Intelligence and Data Analysis Concept (CAIDAC)
Name of the Organizer: Antoine Trad
Department: ICT
University: IBISTM
Country: France
Email: antoine.trad@ibistm.org
Title of the Journal : WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Title of the Special Issue: Enterprise Transformation Projects-Cloud based Artificial Intelligence and Data Analysis Concept (CAIDAC)
Aim:
This article presents the fundaments of the Cloud based Solutions (CbS) which can be used as a basic component of the author’s polymathic transformation framework, especially in the domain Artificial Intelligence (AI) and Data Analysis (DA) services. The implementation of CbS’ AI and DA (CAIDAC) services are supported the author’s Applied Holistic Mathematical Model (AHMM) for CbS (AHMM4CbS) and his various research works on AI and DA AI Services (AIS), Mathematical Models, Cross-functional/Polymathic transformations projects. The AHMM4CbS is based on cross-functional research on an authentic, original, and proprietary mixed research method that is supported by his own version of an AI search tree or the Heuristics Decision Tree (HDT), which is combined with an internal metaheuristic algorithm. In this article the main focus is on CAIDAC’s integration, services’ usage, data management, qualitative analysis, and corresponding transformation strategy. The pro! posed AHMM4CbS based CAIDAC is a virtual decision-making system which uses a real-life case related to business transformation projects. Today such projects needs Cloud platform or infrastructure that is supported by the alignment of various existing commercial Cloud Platform (CP) services, standards, enterprise architecture paradigm, and development strategies. Google’s CP (GCP) was chosen as a sample CP, but there is need to define a standardized architecture methodology, and internal CP procedures so that the organization can build its own Private CP (PCP) and tries to avoid being locked-in and to avoid excessive costs and failure. This article’s main goal is to use a Polymathic-holistic approach to CP and PCP to avoid locked-in situations.
Topics:
Welcome Message from the Organizer:
Dear colleagues I have added an article.
Department: ICT
University: IBISTM
Country: France
Email: antoine.trad@ibistm.org
Title of the Journal : WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Title of the Special Issue: Enterprise Transformation Projects-Cloud based Artificial Intelligence and Data Analysis Concept (CAIDAC)
Aim:
This article presents the fundaments of the Cloud based Solutions (CbS) which can be used as a basic component of the author’s polymathic transformation framework, especially in the domain Artificial Intelligence (AI) and Data Analysis (DA) services. The implementation of CbS’ AI and DA (CAIDAC) services are supported the author’s Applied Holistic Mathematical Model (AHMM) for CbS (AHMM4CbS) and his various research works on AI and DA AI Services (AIS), Mathematical Models, Cross-functional/Polymathic transformations projects. The AHMM4CbS is based on cross-functional research on an authentic, original, and proprietary mixed research method that is supported by his own version of an AI search tree or the Heuristics Decision Tree (HDT), which is combined with an internal metaheuristic algorithm. In this article the main focus is on CAIDAC’s integration, services’ usage, data management, qualitative analysis, and corresponding transformation strategy. The pro! posed AHMM4CbS based CAIDAC is a virtual decision-making system which uses a real-life case related to business transformation projects. Today such projects needs Cloud platform or infrastructure that is supported by the alignment of various existing commercial Cloud Platform (CP) services, standards, enterprise architecture paradigm, and development strategies. Google’s CP (GCP) was chosen as a sample CP, but there is need to define a standardized architecture methodology, and internal CP procedures so that the organization can build its own Private CP (PCP) and tries to avoid being locked-in and to avoid excessive costs and failure. This article’s main goal is to use a Polymathic-holistic approach to CP and PCP to avoid locked-in situations.
Topics:
- Artificial Intelligence
- Machine Learning
- Cloud
- Enterprise architecture
- Mathematical Models
- Development Cycles
- Requirements
- Web Services
- Strategic and Critical Business Systems
- Requirements Engineering
- Business transformation projects
- Organizational Intelligence
- CSFs/areas
- Performance Indicators
- Software (re)engineering
- Strategic Vision
Welcome Message from the Organizer:
Dear colleagues I have added an article.