Detecting negative values where only positives are expected

Filtering for values below zero in a column that should only hold positive numbers is a quick sanity check that surfaces corrupted or mistakenly entered data early.

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Example

Detecting Impossible Negative Retail Values

SELECT *
FROM inventory
WHERE stock_count < 0

Result:

product_id	brand	category	stock_count	price
P2002	UrbanWear	Clothing	-5	49.95
P2004	FreshMart	Grocery	-12	3.49

Step by step

The asterisk symbol means all columns.
```
SELECT *
```
FROM tells SQL which table to pull the data from.
```
SELECT *
FROM inventory
```
WHERE keeps only the rows that match your condition.
```
SELECT *
FROM inventory
WHERE stock_count < 0;
```

Practice

Try each one in your head first, then open the answer.

1. Using orders, write a query to find rows where revenue is negative (a likely data error).

SELECT * FROM orders WHERE revenue < 0

2. Using customers, write a query to find rows where customer_id is negative (a likely data error).

SELECT * FROM customers WHERE customer_id < 0

3. Using products, write a query to find rows where price is negative (a likely data error).

SELECT * FROM products WHERE price < 0

4. Using store_sales, write a query to find rows where revenue is negative (a likely data error).

SELECT * FROM store_sales WHERE revenue < 0

5. Using employees, write a query to find rows where salary is negative (a likely data error).

SELECT * FROM employees WHERE salary < 0

Learn it by doing. This lesson is a short hands-on level on Bampaa: see it work, then build and write it yourself, with instant feedback.

Try this lesson free →

About 5–10 minutes · no sign-up needed