Description

Built a Sales Forecasting Tool for an e-commerce client that predicts future sales based on historical data, seasonal trends, and promotions.

Key Features:

• Predictive Models: Linear regression, ARIMA, and Random Forests
• Data Cleaning Pipelines: Automated handling of missing, duplicate, and inconsistent data
• Visual Dashboards: Interactive charts for trend analysis
• Custom Reports: Scheduled exports and email notifications

Technologies Used:

• Python, Pandas, NumPy, Scikit-learn
• Jupyter Notebooks, Power BI, or Plotly Dash for dashboards
• PostgreSQL for data storage

Design Highlights:

• Visualizations tailored for clarity and impact
• Lightweight UI for easy access by non-technical staff