Published Paper Details:

This paper looks into the integration of data visualization for finance, sales, and predictive analytics using AI/ML techniques in Power BI. The purpose of this research is to explore the capacity to enhance financial decision-making, sales forecasting, and trend analysis that data visualization and machine learning models can potentially create. A large dataset that contains financial, sales, and economic data was considered to demonstrate predictive analytics techniques, which would emphasize time-series forecasting and regression models. The native AI features of Power BI, which include its forecasting tools and the integration of machine learning via Python and R scripts, are used to build precise predictive models. Results reveal that the accuracy of sales and financial predictions increases substantially, key influencers are identified, and actionable insights are made available for decision-makers by the integration of Power BI's interactive dashboards with machine learning models. It demonstrates the advantages of deploying AI-powered visualizations such as decomposition trees and forecasting charts in Power BI for getting complex financial data in view. Data visualization combined with AI/ML techniques integrated with Power BI makes the tool a powerful tool business can use to help it optimize financial analysis and sales prediction