SQL_Project_Music_Store_Analysis
Project Overview - Welcome to the music store data analysis project conducted using SQL! My exploration delves into an extensive dataset comprising 11 tables, including Employee, Customer, Invoice, InvoiceLine, Track, MediaType, Genre, Album, Artist, PlaylistTrack, and Playlist.
Through the application of SQL queries, this project aims to unravel valuable insights and answer numerous critical questions about the music store's operations. By diving deep into the dataset, I aspire to gain profound understanding and enhance decision-making processes within the realm of music retail venture.
Tech Stack Used -
- SQL Server
- SQL Workbench
- Schema: Music Store Database
Usage Import the dataset into your SQL database management system. Run SQL queries located in the SQL_Music_Store_Project.sql file against the database to perform data analysis and generate insights.
Below are the general insights:
- USA is the most popular country for music purchases with 1051 purchases followed by Canada and Brazil with 541 and 432 purchases respectively.
- Rock music is the top selling genre with $26752 spent.
- Queens is the top selling artist.
- Prague has the highest sales volume.
- MPEG audio file sells the most.
- 90's Music is the most popular playlist.
- The month of April had the highest sales.
What I learned -
- Joining tables.
- Using sub queries.
- Using aggregate and ranking window functions.
- Using common table expressions (CTE)
References https://www.youtube.com/watch?v=VFIuIjswMKM (source: www.youtube.com/@RishabhMishraOfficial)
Contributing Contributions to this project are welcome. If you have suggestions for improvements or find any issues, feel free to open a pull request or submit an issue in the repository.