Sales Analysis: Explored music sales data using MySQL and advanced SQL techniques. Derived insights on employee hierarchy, invoices, customer behavior, genres, and country-wise spending. Leveraged JOIN, WHERE, ROW_NUMBER(), and more. Valuable findings on senior employees, best customers, popular genres, and top track bands.
- Utilized MySQL database management system to handle large-scale music sales data effectively.
- Applied various SQL techniques like JOIN, WHERE, and ROW_NUMBER() to extract, filter, and organize data.
- Leveraged advanced SQL features like WITH and WITH RECURSIVE for efficient data manipulation.
- Conducted complex queries to identify senior employees, top invoice values, and highest revenue-generating city.
- Recognized the best customer based on significant expenditure, providing insights for targeted marketing.
- Extracted key information on Rock Music listeners for targeted promotions and recommendations.
- Invited top rock bands to a music festival based on track count for an unforgettable experience.
- Analyzed song durations to create a curated playlist of tracks longer than the average length.
- Calculated customer spending on artists, highlighting the highest expenditure for personalized engagement.
- Determined the most popular music genre in each country, enabling targeted marketing strategies.
- Identified the top customer in each country based on music spending, fostering customer loyalty.
The analysis in this project offers meaningful insights into music sales trends, customer preferences, and revenue generation. By applying SQL techniques effectively, we were able to extract actionable insights from the vast music sales dataset.
Contributions to this project are welcome! If you discover any issues, have suggestions, or want to add new analyses, please feel free to open an issue or submit a pull request.
For detailed insights and in-depth analysis of the Music Sales project, please refer to the 'description' folder in this repository."
For any inquiries or feedback, please contact me at www.linkedin.com/in/yogendra-wadkar.