The Influence of Kanban Project Management Methodology Success Factors on Data Science Project Teams
The British University in Dubai (BUiD)
The current study targeted the issue of Kanban methodology integration for the needs of effective management of Data Science project teams. The rapid growth in the number of Data Science projects that are being implemented in the contemporary world has increased the relevance of the study in this sphere. It is vital to develop effective and reliable project management methods that can enhance the productivity and quality of cooperation among members of a Data Science project team. To address this question, the researcher reviewed the following key variables: Data Science project team challenges, and success factors of the Kanban methodology. It was important to estimate the potential influence of specific challenge factors on the performance of the Data Science project teams. In addition, the role of Kanban success factors as instruments of mitigating and preventing challenges was assessed. The results of the study were based on the collection of survey data from the target population of project managers and other members of the Data Science project teams. The data analysis methods included descriptive statistics and regression analysis. The study outcomes demonstrated the effectiveness of the Kanban methodology in dealing with some pre-identified project management challenges in the field of Data Science. The study produced a significant premise. This suggests that the target population may not have the necessary knowledge and experience to effectively benefit from the Kanban project management techniques. Further research will be required to evaluate this premise.
data science, agile project management, Kanban methodology, regression analysis, project management