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Part A

Since Part A was mainly just to generate data, I used my resources (ChatGPT) to generate most of the data, and then I went back and changed a few things that were incorrect.
I don’t see much ‘helpfulness’ of creating the data myself, since it’s a largely menial task which will produce pretty similar results of just asking ChatGPT to generate data. I had to also go back and ensure that the data was ‘realistic’, so I made sure to double check everything.

Part B

For the analysis, it was pretty straightforward. The only thing I needed to ensure was that the species was not null, since there were certain sales items in which it was for products, rather than pets (so I did a JOIN rather than a LEFT JOIN). Interestingly, there are ‘duplicate species’, but that’s just due to different sale locations for each species—since you can purchase species at different locations.

This analysis was pretty straightforward as well; I just utilized the COUNT, SUM, and AVG functions with data from Products table. The category habitat has the most total. Also, I added a out_of_stock column, which indicates the number of products that are out of stock within that certain category.

This was pretty simple, I just did the number of total purchases (with the COUNT). Also, I added the total spent and the average purchase for each planet. Interestingly, Earth is the planet with the highest total spent, although it has the second highest average purchase.

For this, it was pretty simple to get the actual data. However, to extract the actual ‘month’, formatted nicely, I used the FORMAT function, with MMMM as the second argument to display the entire month name.

This one was pretty simple as well, I just got the total transactions, the total revenue, and the average transaction for each payment method. The highest average transaction is credit, followed by cash, and then debit.

This is pretty similar to another part within this lab. I did a few functions, such as SUM, AVG, and COUNT. The species that has the highest revenue is the Canine species, followed by Aquatic, and then Avian. As for the popularity, I just thought that it would be the total sales volume—since I wasn’t sure how else the popularity would be ranked, unless there was a rating between 0 and 10, but I wasn’t sure how that would be implemented, unless you had a complex fucntion.

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