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

# Fabricate

> Build synthetic datasets from scratch by defining tables and columns with data generators.

Fabricate lets you create a test database from a blank canvas. You define each table and column yourself, and assign a data generator to populate each field. There is no source datasource required.

Use Fabricate when you need a custom dataset that doesn't map to an existing production schema.

## Create a test database

1. Navigate to **Test Data → Fabricate** in the left sidebar.
2. Click **New Database**.
3. Enter a **Database Name**.
4. Click **Submit**.

## Database View

The Database View is where you build your tables and configure column generators.

### Add a table

Click **New Table** in the top navigation bar. Choose how to create the table:

| Option            | Description                                                                                                                  |
| ----------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| **Table**         | Import columns from an existing datasource table. Select a datasource, then a dataset, then choose which columns to include. |
| **View**          | Import columns from a datasource view. Select a datasource, then a view, then choose columns.                                |
| **Virtual Table** | Add a pre-built virtual table. All columns are included automatically.                                                       |

### Configure a column

Click the edit icon on any column to open the column editor:

| Field               | Description                                                                                                             |
| ------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| **Column Name**     | Name of the column.                                                                                                     |
| **Generator**       | The data generator to use. Search by name or browse by category. Each generator shows a description and example output. |
| **Hide Column**     | If enabled, this column is excluded from the generated output.                                                          |
| **Unique**          | Enforce uniqueness across all generated values for this column.                                                         |
| **Null Percentage** | Percentage of rows that will contain a null value (0–100).                                                              |
| **Format**          | Optional format pattern for the generated value.                                                                        |
| **Mask**            | Optional mask pattern applied to the value.                                                                             |

### Generator types

| Generator                     | Description                                                                                                |
| ----------------------------- | ---------------------------------------------------------------------------------------------------------- |
| **Standard generators**       | Email, phone, name, address, and more. See [Test Data Generators](/reference/functions) for the full list. |
| **value\_of\_column**         | Copies values from a specific column in a connected datasource. Select the dataset and column.             |
| **custom\_function**          | An AI-generated function based on the column name.                                                         |
| **similar\_values**           | Generates values similar to a list of examples you provide.                                                |
| **category\_value**           | Generates values from a selected category.                                                                 |
| **value\_of\_virtual\_table** | Draws values from a pre-built virtual table.                                                               |

### Add a column

Click **Add Column** within any table to add a new column and assign a generator to it.

### Row count

Click the edit icon next to the row count in the column table header to set how many rows to generate for each table.

## Table View

The Table View previews the generated data. Select a table from the left sidebar to see a sample of the generated rows.

From here you can:

* **Download Data** — Save the generated dataset as a file.
* **Export YAML** — Export the generator configuration for reuse or version control.
* **Regenerate Data** — Trigger a new generation run with the current configuration.

## Foreign Keys

Define relationships between tables to maintain referential integrity in the generated data.

Click **New FK** to create a relationship:

* **Foreign Key** — Select the table and column that holds the foreign key.
* **Primary Key** — Select the table and column it references.

## Data Targets

Data Targets define where the generated data is delivered — for example, an API endpoint or webhook.

| Field            | Description                              |
| ---------------- | ---------------------------------------- |
| **Name**         | A label for this target.                 |
| **Request Type** | HTTP method — GET, POST, PUT, or DELETE. |
| **Link**         | The endpoint URL.                        |
| **Headers**      | Key-value pairs added to the request.    |
| **Request Body** | JSON payload sent with the request.      |
| **Target Type**  | The type of destination.                 |