This project develops a Power BI platform integrating Python and machine learning models (ARIMA, SARIMA, LSTM) to forecast sales, optimize inventory, and drive strategic decisions. It offers real-time dashboards, key KPIs (e.g., GMROI, sales velocity), and actionable insights, with scalability for diverse retail sectors. Stakeholder feedback has been incorporated, and the models are successfully deployed. Next steps include final integration, automation, and client delivery.
Keywords: Retail Analytics, Sales Forecasting ,Data-Driven Insights, Business Intelligence
Tools: Python, SQL,Colab,PowerBI,Excel
Department: Department of Business Studies
Tools: Python, SQL,Colab,PowerBI,Excel
Department: Department of Business Studies
Project Poster
