This project focuses on analyzing retail order data using SQL and Python to uncover key business insights. The analysis covers various aspects such as identifying top-selling products, tracking revenue trends, and understanding regional sales performance. By combining SQL queries for data extraction and Python scripts for data processing, this project demonstrates a robust approach to solving real-world business problems.
- Identify top revenue-generating products.
- Analyze the best-selling products in different regions.
- Track month-over-month sales growth for 2022 and 2023.
- Leverage SQL for efficient querying and Python for additional analysis.
- SQL: Data extraction, aggregation, and querying.
- Python: Data processing and visualization.
- Jupyter Notebook: For scripting and analysis.
- Kaggle API: For dataset retrieval.
The dataset used is sourced from Kaggle and contains retail order details such as order date, product information, sales figures, and regional data.
Dataset link: Here