> For the complete documentation index, see [llms.txt](https://docs.whaly.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.whaly.io/data-management/workbench/understanding-datasets/relationships.md).
# Relationships
Relationship are a way of telling Whaly how your datasets are linked together.
It's a great way to:
* Combine data from various source
* Create detailed explorations
## How can I configure relationship?
To configure a dataset relationship, go to the **information** tab and then scroll to the relationship block and click on **Add a relationship.**
Adding relationships
In order to add a relationship you need to provide:
* A dataset which will be related to the current dataset
* A column from the current dataset
* A column from the related dataset that will match the one selected above in values and in type (example => String can only match String columns)
* A type of relationship
* Has many
* Belongs to
* Has one
## Understanding Relationship Type
Let's imagine we have the three following tables:
**Orders**
```
| order_id | amount | user_id |
|----------|----------|----------|
| 1 | 90 | 1 |
| 2 | 10 | 1 |
| 3 | 50 | 2 |
| 4 | 30 | 1 |
| 5 | 20 | 2 |
```
**Users**
```
| user_id | name | address_id |
|----------|-----------------|-------------|
| 1 | Rick Sanchez | 1 |
| 2 | Archer Sterling | 2 |
```
**Address**
```
| address_id | name |
|-------------|----------------------|
| 1 | 6910 Smith Residence |
| 2 | Penthouse NYC |
```
In this example a User has multiple orders therefore when setting up relationships we will do:
**Relationship 1:**
* **From dataset**: User
* **To dataset:** Order
* **Type** has many
* **From Column**: user\_id
* **To column**: : user\_id
Please note that **"has many"** is the opposite of **"belongs to"**, therefore this relationship would have been legit too:
**Relationship 2:**
* **From dataset**: Order
* **To dataset:** User
* **Type** belongs to
* **From Column**: user\_id
* **To column**: : user\_id
{% hint style="info" %}
Whenever a relationship is created, the symmetric relationship is automatically created on the other dataset.
{% endhint %}
As we have the same number of rows in both the Users and Address as a User can have a single Address and vice versa, we will create a one to one relationship:
**Relationship 3:**
* **From dataset**: User
* **To dataset:** Address
* **Type:** has one
* **From Column**: address\_id
* **To column**: address\_id
{% hint style="warning" %}
The "has one" relationship is quite rare in real world, it's relevant when you have exactly the same number of rows in the two related datasets.
{% endhint %}
---
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