> ## Documentation Index
> Fetch the complete documentation index at: https://docs.squared.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# SQL Editor

> SQL Editor for Data Modeling in AI Squared

## Overview

AI Squared's SQL Editor allows you to define and manage your data models directly through SQL queries. This powerful tool supports native SQL commands compatible with your data warehouse, enabling you to seamlessly model your data.

## Creating a Model with the SQL Editor

### Starting with a Query

Begin by writing a SQL query to define your model. For instance, if using a typical eCommerce dataset, you might start with a query like:

```sql theme={null}
SELECT * FROM sales_data.customers
```

### Previewing Your Data

Click the `Preview` button to review the first 100 rows of your data. This step ensures the query fetches the expected data. After verifying, proceed by clicking `Continue`.

<Tip>**Important Note:**  The model cannot be saved if the query is incorrect or yields no results.</Tip>

### Configuring Model Details

Finalize your model by:

* Naming the model descriptively.
* Choosing a column as the Primary Key.

### Completing the Setup

Finish your model setup by clicking the `Finish` button.

## Unique Primary Key Requirement

Every model requires a unique primary key. If no unique column exists, consider:

* Removing duplicate rows.
* Creating a composite column for the primary key.

## Handling Duplicate Data

To filter duplicates, use a `GROUP BY` clause in your SQL query. For instance:

```sql theme={null}
SELECT *
FROM customer_data
GROUP BY unique_identifier_column
```

## Composite Primary Keys

In scenarios where a unique primary key is not available, construct a composite key. Example:

```sql theme={null}
SELECT customer_id, 
       email, 
       purchase_date,
       MD5(CONCAT(customer_id, '-', email)) AS composite_key
FROM sales_data
```

## Saving a Model Without Current Results

To save a model expected to have future data:

```sql theme={null}
UNION ALL
SELECT NULL, NULL, NULL
```

Add this to your query to include a dummy row, ensuring the model can be saved.

## Excluding Rows with Null Values

To exclude rows with null values:

```sql theme={null}
SELECT *
FROM your_dataset
WHERE important_column1 IS NOT NULL AND important_column2 IS NOT NULL
```

Replace `important_column1`, `important_column2`, etc., with your relevant column names.