Let’s consider the following `income_table` table that stores the `income` and `debt` values.

``````SELECT income, debt
FROM income_table;
``````

On execution, we get:

``````+------+-----+
|income|debt |
+------+-----+
|60000 |20000|
|80000 |25100|
|100000|30040|
|120000|36010|
+------+-----+
``````

A simple visualization of the data present in the `income_table` table is as follows: Querying the income table to get the `debt` value for a particular `income` value results in the following:

``````SELECT income, debt
FROM income_table
WHERE income = 80000;
``````

On execution, we get:

``````+------+-----+
|income|debt |
+------+-----+
|80000 |25100|
+------+-----+
``````

And here is what we get: But what happens when querying the table for an `income` value that is not present there?

``````SELECT income, debt
FROM income_table
WHERE income = 90000;
``````

On execution, we get:

``````Empty set (0.00 sec)
``````

When the `WHERE` clause condition is not fulfilled for any of the rows, no value is returned. When a table doesn’t have an exact match, the query returns an empty set or null value. This is where the AI Tables come into play!

Let’s create a `debt_model` model that allows us to approximate the `debt` value for any `income` value. We train the `debt_model` model using the data from the `income_table` table.

``````CREATE MODEL mindsdb.debt_model
FROM income_table
PREDICT debt;
``````

On execution, we get:

``````Query OK, 0 rows affected (x.xxx sec)
``````

MindsDB provides the `CREATE MODEL` statement. On execution of this statement, the predictive model works in the background, automatically creating a vector representation of the data that can be visualized as follows: Please note that `debt_model` is our AI Table.

Let’s now look for the `debt` value of some random `income` value. To get the approximated `debt` value, we query the `mindsdb.debt_model` model instead of the `income_table` table.

``````SELECT income, debt
FROM mindsdb.debt_model
WHERE income = 90000;
``````

On execution, we get:

``````+------+-----+
|income|debt |
+------+-----+
|90000 |27820|
+------+-----+
``````

And here is how it looks: 