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Information Technology (IT) governance is a combination of processes and controls to increase the success rate of projects, programs, and portfolios. We have several research articles evidencing the stability of classification techniques into medical, security, sports, artificial intelligence, software project management, etc. The utilization of classification techniques such as Naïve Bayes algorithm in software governance has unique advantages in terms of accuracy. The approach in this article would help to provide key management insights to make precise decisions and improve the overall success rate of the software projects, programs and portfolios.
Naïve Bayes algorithm is used to logically validate the alignment of governance policies and project details through Weka (Waikato Environment of Knowledge Analysis). Weka is a collection of machine learning algorithms for data mining tasks. IT governance policies are used as a benchmark for validation and processed with Naïve Bayes algorithm in Weka
Governance team members would be an interface to communicate and set expectations with the project manager. Basic governance standards across Software Development Lifecycle (SDLC) are defined and used as a bench mark in the governance assessment form. These predefined governance assessment forms and project details are validated through Naïve Bayes algorithm. This proactive model and adherence to the governance standards would help to increase the success rate of IT projects.