> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/functionality/data-set/combining-data/join-data.md).

# Join data

Coupler.io allows you to fetch data from several sources at the same time, and join them into a unified dataset - all with a single importer.

Data **JOIN** is a term Coupler.io uses to describe the process of combining two or more sources using LEFT JOIN (from SQL terminology) - meaning, all the elements from the left set are kept while only matching elements from the right set are included

{% embed url="<https://www.youtube.com/watch?v=ZOi7mzr0e3c>" %}

### How to join data from multiple sources? <a href="#how-to-join-data-from-multiple-sources-7yscp" id="how-to-join-data-from-multiple-sources-7yscp"></a>

Let's take this example to understand this feature further. We have these source tables:&#x20;

{% columns %}
{% column width="58.333333333333336%" %}
*Source 1: Contacts*

<figure><img src="/files/8pmgOjjrgcuR5ZfMih3B" alt="" width="563"><figcaption><p><em>Contacts</em></p></figcaption></figure>
{% endcolumn %}

{% column width="41.666666666666664%" %}
*Source 2: Department*

<figure><img src="/files/HpzgdQHAiBzSeIwdIeDG" alt="" width="369"><figcaption><p><em>Department</em></p></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

**Goal**: We want to get a list of "Contacts" under the "Partner sales" department. Currently, the "Contacts" table only has the IDs.

{% @arcade/embed flowId="l8nSlkOARJd5A6WlsqIz" url="<https://app.arcade.software/share/l8nSlkOARJd5A6WlsqIz>" %}

{% stepper %}
{% step %}
After adding the needed sources, go to the "Transformations" step and either select Join data from the data preview window, or hit + Add transformation >> Create Join option from the left sidebar
{% endstep %}

{% step %}
Select the sources to join and the columns that will be used as the key:
{% endstep %}

{% step %}
Click the "Join data" button and we will get the following results:
{% endstep %}

{% step %}
After joining the data, you can apply [other transformations](/functionality/data-set/preview-data-and-data-sets.md) such as: hide and reorder columns, filter and sort data, add a formula column, etc. to achieve the desired result:
{% endstep %}
{% endstepper %}

#### 1. Order of key source matters <a href="#key-order" id="key-order"></a>

Let's review 2 sources

{% columns %}
{% column width="58.333333333333336%" %}
*Source 1: Users data*

<figure><img src="/files/GDyli5d1ZbYpyX5kNXre" alt="" width="375"><figcaption><p>Users data</p></figcaption></figure>
{% endcolumn %}

{% column width="41.666666666666664%" %}
*Source 2: Additional user data*

<figure><img src="/files/29F3R4tP5y2J24Y8Ptqm" alt=""><figcaption><p>Additional user data</p></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

As we can see, both of the tables contain "Id" column representing the user id. But, together with that, amount of rows is different: 10 and 3 respectively

* In case "Users data" is chosen as the Key source, we will receive the next result (10 rows as in the key source):

<figure><img src="/files/uDhiQm1WKqT6rAvH1zJQ" alt=""><figcaption></figcaption></figure>

* In case "Additional user data" is chosen as the Key source, we will receive the next result (3 rows as in the key source):

<figure><img src="/files/n93ZG0s4yyHKQeIUSK71" alt=""><figcaption></figcaption></figure>

#### 2. Join by multiple fields <a href="#join-by-multiple-fields" id="join-by-multiple-fields"></a>

Along with Join by 2 sources, it is possible to join these sources by multiple fields

{% columns %}
{% column width="58.333333333333336%" %}
*Source 1: Users data*

<figure><img src="/files/A7q4U35nA9icot1bE4S0" alt=""><figcaption><p>Users data</p></figcaption></figure>
{% endcolumn %}

{% column width="41.666666666666664%" %}
*Source 2: Additional user data*

<figure><img src="/files/pgFdn1wf7cOLurf6BvcE" alt=""><figcaption><p>Additional user data</p></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

First, let's join these 2 sources by the "Id" field. The result will look like this (part of the data from "Additional user data" was cut due to missing references in the key source):

<figure><img src="/files/dxhv6ku6u8SiVlcKTgT7" alt=""><figcaption></figcaption></figure>

Next, we can join these 2 sources by one more column "Name".&#x20;

<div align="left"><figure><img src="/files/gY6jNnOvoWXH0PKkFPg6" alt="" width="375"><figcaption></figcaption></figure></div>

The result of both joins will look like this (first column changed):

<figure><img src="/files/6BIiYA6KbXFLpcnNatGd" alt=""><figcaption></figcaption></figure>

As a next step, we can clean up (filter out) results a bit and leave only rows that contain data. Also, we can hide some columns to have no duplicates.

<div align="left"><figure><img src="/files/SMZ3A8Py3E9fsfXJkL95" alt="" width="375"><figcaption></figcaption></figure></div>

And receive beautified results:

<figure><img src="/files/Y50MrCsj40IA2uHfOGaW" alt=""><figcaption></figcaption></figure>

#### 3. Join by multiple sources <a href="#join-by-multiple-sources" id="join-by-multiple-sources"></a>

**Goal:** We wanted to get a list of user names from the "Users" table, the amount of sold products from the "Transaction data" table, and product categories from the "Product data" table.

{% columns %}
{% column %}
*Source 1: Users data*

<figure><img src="/files/c90bYV7ulzSKCg3FfymY" alt=""><figcaption><p>Users Data</p></figcaption></figure>
{% endcolumn %}

{% column %}
*Source 2: Transaction data*

<figure><img src="/files/P3C0NusqtTiCvCbsI13Q" alt=""><figcaption><p><em>Transaction data</em></p></figcaption></figure>
{% endcolumn %}

{% column %}
*Source 3: Product data*

<figure><img src="/files/pwp2gfGU7cWtlx309Y7O" alt=""><figcaption><p><em>Product data</em></p></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

Next data join setup will produce the desired result:

<div align="left"><figure><img src="/files/SDPIUM0a2VBExb8gTTQs" alt="" width="375"><figcaption></figcaption></figure></div>

After applying data join along with the current transformation capabilities, the goal was achieved:

<div align="left"><figure><img src="/files/oV8oM5RkjFM5m1PITNV8" alt="" width="375"><figcaption></figcaption></figure></div>


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