Scaling Up the Agility of Data Management by Scaled Agile Data Management Framework (SADMF)

The research aims to design a scalable agile data management framework leading to the success in data-oriented decision-making and ultimately smartness and data intelligence using agile manifesto and scalability. The main paradigm is data-driven, lean thinking and agile manifesto. As an applied and developmental research, argument, analogy and discovery are used to draw conclusions. In this research Design Science Research Methodology (DSRM) is applied. Thus, firstly, the problem was defined clearly via literature review. Secondly, objectives of solution were specified specifically. Thirdly, the artifact (SADMF) was designed and developed via iterations through SCRUM. Fourthly, validity and reliability were evaluated by SMEs and finally the results were formalized and academics and practitioners were invited to consider reflective thinking. There are various reference models for the concepts of agile, data management, Information System and Software Engineering, but few of them practically embedded agile practices in a scalable management system, despite the remarkable importance of agility in the optimal data management of social-physical-cyber systems today. So, there is an essential need to design a comprehensive model. Scaled agile data management requires leanness and agility. This framework has three levels including portfolio, program and data lab and four main elements including people and organization, agile process and practice, technology and knowledge areas. Finally, considering the selected references, a Scalable Agile Data Management Framework (SADMF) from combination of agile best practices along with the main elements of a data management system was designed and offered.