A fictional music company has asked us to analyze their database to see where we can improve and maximize profits. Using the Chinook music database, we can explore a realistic dataset and build complex queries to simulate a real-world analysis of a fictional music company. In this project we will construct complex SQL queries to help us maximize profits. The questions we aim to answer in this project are the following:
- Which genres sell the most tracks in the U.S.?
- How are the sales support agents performing?
- Can we collate data on purchases from other countries?
- What do customers buy more of: whole albums or individual tracks?
- What artist is used in the most playlists?
- What percentage of tracks have been purchased vs. not purchased?
- Do customers care about protected vs. non-protected media?
Along the way, we will not only query the database, but also read it in to a pandas DataFrame for visualization, making our query results easier to digest.
To view the notebook, click on the .ipynb file above, or view it here.