Develop a predictive analytics system that forecasts future sales and revenue using historical transaction data. The project will help businesses make informed decisions about inventory, marketing strategies, and financial planning using machine learning models and interactive dashboards.
Collect historical sales and revenue datasets from sample retail or e-commerce systems.
Perform data cleaning, normalization, and preprocessing.
Conduct exploratory data analysis to identify trends and seasonality.
Implement forecasting models such as Linear Regression, ARIMA, or LSTM.
Compare model accuracy using evaluation metrics like RMSE and MAE.
Build interactive dashboards using Power BI or Tableau to visualize predictions.
Generate insights for inventory optimization and marketing strategy planning.
Test system performance with different datasets.
Document methodology, models used, performance results, and business recommendations.
