In this project, I built SQL queries and subqueries on a music store’s relational database to identify targeted insights based on business requirements and report on them with technical analysis and visualizations. This results in the delivery of actionable conclusions using business acumen and accurate data manipulation in SQL.
- How many customers and how much in sales does each sales rep bring in?
- What is the most common media type for all music files?
- What are the sales and number of customers by state in the USA?
- What is the most popular genre for each state in the USA?
- What is the most popular artist for each state in the USA?
Download the chinook.db locally. I performed my queries in SQLite, but you can use SQL Server, Oracle, MySQL, PostgreSQL, or DB2 as well.
Find any typos? Any improvements to my queries or additional queries you'd like to add? Contributions are welcome.
First, fork this repository.
Next, clone this repository to your desktop to make changes.
$ git clone https://github.com/ccaddel/music_database_insights.git
$ cd music_database_insights
Once you've pushed changes to your local repository, you can issue a pull request by clicking on the green pull request icon.
Instead of cloning the repository to your desktop, you can also go to README.md in your fork on github.com, hit the Edit button (button with the pencil) to edit the file in your browser, then hit the Propose file change button, and finally make a pull request.
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