What is Industrial Information Integration Engineering

There is an overestimation of the benefits that may be provided by machine learning (ML) applications. Recent studies report the failures of ML projects, inadequate return on investment, or unsatisfactory project outcomes. Software engineering challenges, business and IT alignment, holistic management of business processes, data, applications, and infrastructure may be some causes. However, the author believe that the integration of ML applications with enterprise components is a serious issue that is often neglected. Therefore, the main argument of this study is that the enterprise integration models are critical for the long-term benefits and sustainability of ML-driven systems. In this study, the author developed an enterprise integration method for ML-driven business systems by using enterprise architecture methods and tools. Finally, this method is applied to an online shopping system in a business case study and presented important findings and insights.