IS NOT NULL

NOT NULL performs the exact opposite of the IS NULL evaluation. It will drop all records in the table whose column of evaluation has NULL values. This can be useful if the data or analysis you are performing required every observation to have data.

To demonstrate this on a query, let's modify the previous query that returned records from the orders table whose freight information has null values but ship_country is not null to now return only customers order_id, customer_id, ship_country, order_date with missing freight details. The query would look like this:

select order_id, customer_id, ship_country, order_date, freight
from orders
where freight IS NULL AND ship_country IS NOT NULL

| order_id | customer_id | ship_country | order_date | freight |
| -------- | ----------- | ------------ | ---------- | ------- |
| 3024     | 2024        | Austria      | 2023-05-05 | null    |
| 3029     | 2029        | Denmark      | 2023-06-01 | null    |

The above results only contain values with valid region data.

Making use of NULL evaluations is an important practice to validate information and analysis particularly if the analysis is intended to drive a key decision. Null values happen for many reasons and your ability to filter can allow you to have accurate analysis and insights for decision making.

In the next section, we look at filtering text with the LIKE Operator.