Development and Integration of Scrum Tree Algorithm with K-means Data Clustering

Abstract

The goal of project management is usually to anticipate or perhaps estimate as most potential issues and so complications as conceivable; and then to approach, coordinate and restrain actions in order that the tasks accomplished as effectively as plausible in spite of each associated risk. To deal with upcoming era initiatives, Scrum and agile platform is indicating the ideal. Scrum project control is a method for controlling software execution that originates beneath the wider umbrella of agile assignment control. It gives a light and portable procedure framework which usually holds iterative as well as, progressive methods; assisting businesses achieve functioning software even more often. Scrum is definitely an agile software advancement method engineered to put strength, target, quality, and openness to project groups producing software products. It harnesses fabricated life analysis by permitting groups to function in close proximity to the border of commotion to promote speedy system progress. Consequently, presently there is a need of project management tool integration with new scrum tool facilities. This paper presents the k-means data clustering integration with our developed scrum tree algorithm and also the integration for efficient project management. The results show that the proposed research is better than the existing project development model.