Given the following three tables with the given data:
The bookstore manager wants to analyze premium-priced books across all sections of the store. They're particularly interested in books priced above $20 to understand the distribution of higher-priced inventory across different categories. This information will help them make informed decisions about pricing strategies and premium book displays.
@ -101,11 +104,49 @@ Your output should look like this:
```sql
SELECT id, title, price, 'Fiction' as section
FROM fiction_book WHERE price > 20
FROM fiction_book
WHERE price > 20
UNION
SELECT id, title, price, 'Non-Fiction' as section
FROM non_fiction_book WHERE price > 20
FROM non_fiction_book
WHERE price > 20
UNION
SELECT id, title, price, 'Summer Read' as section
FROM summer_read WHERE price > 20
FROM summer_read
WHERE price > 20
ORDER BY section, price DESC;
```
### Explanation
Let's break down how this query works:
First, we get expensive books from the fiction section:
```sql
SELECT id, title, price, 'Fiction' as section
FROM fiction_book
WHERE price > 20
```
Then we use `UNION` to combine results with expensive non-fiction books:
```sql
UNION
SELECT id, title, price, 'Non-Fiction' as section
FROM non_fiction_book
WHERE price > 20
```
And finally, we add expensive books from the summer reading list:
```sql
UNION
SELECT id, title, price, 'Summer Read' as section
FROM summer_read
WHERE price > 20
```
The `UNION` operator combines the results from all three queries while removing any duplicates. We add a literal string value as 'section' to identify which table each book comes from.
This query helps the manager understand the distribution of premium-priced books across different sections, which can inform decisions about pricing strategies and store displays.
You have access to two tables: `trending_book` which tracks currently popular books across all genres, and `tech_book` which lists programming and technology books.
The bookstore's marketing team wants to boost sales in the technology section. They've noticed some tech books aren't getting as much attention as others and want to identify which technical books aren't currently trending. This information will help them plan targeted promotions and display adjustments to increase visibility for these underperforming titles.
> `trending_book` table shows currently trending books:
@ -59,11 +59,11 @@ You have access to two tables: `trending_book` which tracks currently popular bo
| 4 | Python Crash Course | Python | 34.99 |
| 5 | Head First Java | Java | 44.99 |
Write a query to find the technical books that are not currently trending. **Hint:** you can use one of the set operations.
Write a query to identify technical books that aren't currently in the trending list. The marketing team wants to see:
## Expected Results
- The title of each non-trending technical book
Your query should return:
## Expected Output
| title |
| -------------------------- |
@ -78,5 +78,35 @@ SELECT title
FROM tech_book
EXCEPT
SELECT title
FROM trending_book;
FROM trending_book
ORDER BY title;
```
### Explanation
Let's break down how this query works:
First, we get all titles from the technical books catalog:
```sql
SELECT title
FROM tech_book
```
Then we use `EXCEPT` to remove any titles that appear in the trending books list:
```sql
EXCEPT
SELECT title
FROM trending_book
```
The `EXCEPT` operator returns all rows from the first query that don't appear in the results of the second query. This effectively gives us all technical books that aren't trending.
Finally, we order the results alphabetically:
```sql
ORDER BY title
```
This query helps the marketing team identify which technical books might need additional promotion or better placement in the store. They can use this information to create targeted marketing campaigns or special displays for these books to increase their visibility and sales.
Kamran Ahmed
4 weeks ago