2. Identify an interesting website with a publicly available API that returns JSON data.
4. Analyze the data by hand, and describe one or more relational tables that you could load a portion of the data into. You don't need to populate the table(s), but you should describe the table and columns. Consider providing a SQL script and/or an ER diagram to describe the table structure(s).
6. Identify a use case for an organization that would benefit from including this web-based data in its analytics efforts. Oftentimes, a lot of value can be created by combining an organization's proprietary data with other freely available data!

Below is a sample solution. You may use another New York Times API or an API from a different website in your discussion.

After searching the web for New York Times API, I signed up for a (free) API key, then created this query to return JSON data about best-selling books by Miami-based author Carl Hiaasen:

https://api.nytimes.com/svc/books/v3/lists/best-sellers/history.json?api-key=a68e40e07a7f478cb8283104cfa77e5e&author=Carl%20Hiaasen

After studying the JSON, I determined that I might create a single Postgres table that contains each book's title, description, and author. I would have liked to also include the price attribute, but I saw that it was not populated. A more complicated analysis might be to also analyze the JSON data and indicate the number of weeks each book was on the New York Times best-seller list and the top rank that the book achieved.

A sample use case: a book editor might want to analyze descriptions of all of the recent best-selling books in the same genre that he or she specializes in to determine which new authors' books are most likely to become future best sellers.

Search any website that provides APIs. Then determine how many attributes are useful to create a table. Last, write one or 2 analyses can be done with that data Please send a solution asap.