A bookshop hired you as their data scientist and would like you to help them make better business decisions using data.

Here is the data file they provided to you.

Last week, you explored the data and came up with three important questions (or KPI - key performance indicators) that you think you can derive an answer from this data set.

This week, we will get the data ready for visualization.

Step 1 - Please choose three of the questions below. Questions listed in one-row count as one question.

1. What books are the most popular? The least popular? Is that based on sales, reviews, checkouts, or another metric?
2. Who was the youngest debut author? Who was the oldest?
3. Do some publishing houses seem to specialize in any way?
4. What was the longest time between editions of the same book?
5. Are there any seasonal trends for sales? What about checkouts? Do any titles or genres have seasonal fluctuations?
6. Are there any correlations between checkouts, print run size, book review ratings, and sales volume?
7. Do the authors who spend the most time writing have the most successful books? Do they have the highest page count?
8. When are most books published? Are there any anomalies?
9. Are there any trends for genre, format, and price?
10. What sort of distributions do the ratings have? Do those distributions vary by book? By genre? Do they seem to align with awards?
11. How would you calculate the sales price, given that there is sometimesbut not alwaysa discount given at the time of sale?
12. Do sales approximate the Pareto principle?
13. Are there any patterns in the discounts?

Step 2 - Please list all the tables required to answer each question you chose. And write down the table's connection type (relate, join, blend, union) in a Word Document.