This report seeks to answer several questions about our data. The questions are answered with SQL queries on a 15 table database for a DVD rental company and were then visualized using plotly and RMarkdown. The questions included:
Which films are most costly to replace and why?
Over time, how often are the different ratings and categories of films rented?
Over time, how do the performances of the different stores compare?
What is the current total balance of all of our customers?
The data itself is synthetic and can be found here. For this report, I hosted the database locally to perform the queries. The full project and code can be found here if you would like to reproduce any of the analysis.
Of the 1000 films in the database, the average film costs about $19.98 to replace and the individual costs range from $9.99 to $29.99. To get an intuition of why films might be more expensive to replace, it can be helpful to explore the table (Figure 1) below where films are sorted by their replacement cost. It is difficult to learn much this way but as will be shown, there may not even be a definitive connection between a film’s characteristics and its replacement cost.
Language ID and
Release Year each only have a single unique value across all of the data.