A Study of Employee Performance and Project Analytics in the IT Industry Using Power BI and AI/ML

Managing employee performance and analyzing project progress are essential for improving efficiency in the Information Technology (IT) industry, where meeting deadlines and using resources effectively are highly important. However, many IT organizations still face issues such as uneven workload distribution, lack of real-time performance tracking, project delays, and limited use of modern analytical tools. This study explores how data-driven approaches, particularly Power BI and Artificial Intelligence/Machine Learning (AI/ML), can help improve employee performance and project outcomes. The study mainly focuses on factors such as employee productivity, workload balance, use of performance dashboards, project monitoring, and the role of AI/ML techniques. It examines how these elements contribute to better project success, improved efficiency, smarter decision-making, and effective use of resources. A descriptive research design is used for this study, combining both primary and secondary data. Primary data is collected through a structured questionnaire from IT professionals, while secondary data is obtained from research papers, reports, and other relevant sources. The collected data is analyzed using basic statistical techniques such as percentages and correlation, along with visual representation through dashboards. The findings highlight that combining Power BI with AI/ML provides better insights into employee performance, supports effective project management, and helps organizations make more informed, data-based decisions. This study offers useful insights for managers, professionals, and researchers working in the IT domain.