This is the landing page showcasing a SQL project I conducted as part of my completion of the 4-month "Programming for Data Science with Python" nanodegree - an online coding bootcamp by Udacity. For this project, I queried a local copy of the PostgreSQL sample database, Sakila, which contains data from a DVD rental company. I restored a copy of this database to my own local instance of PostgreSQL and executed the SQL queries through the pgAdmin interface.
I queried the database to create several aggregations of the data, including summations of number of rentals for family genre movies, quartiles of rental durations, and counts of rentals by stores.
To uncover these insights, I used all of the common SQL functions, including joins and aggregations, as well as more complex common table expressions and window functions.
You can review a written report of my findings, including Excel-generated charts, for a summary of the findings here.
And here is the SQL code I wrote to generate the insights summarized in the report.