---
title: Understanding data blending in Google Looker Studio
description: If you’re a Google Data Studio advanced user, I'm sure you’ve already used the data blending feature. 2. Click on Resource ➞ Manage blends ➞ +Add a blend 3. One of your data sources will be added a
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June 11, 2024
# Understanding data blending in Google Looker Studio
If you’re a Google Data Studio advanced user, I'm sure you’ve already used the data blending feature.
> ### What is data blending?
#### Data blending lets you create charts, tables, and controls based on multiple data sources in the same dashboard.
> ### How blending works step by step
#### Creating a new blended connector
- *If you already know how to create a blended connector you can [skip these steps](https://support.dataslayer.ai/understanding-data-blending-in-google-data-studio#Configuring-our-dashboard).*
1\. Make sure you have 2 or more active [connectors](https://lookerstudio.google.com/data?search=softpoint) on your Google Data Studio dashboard.
.png?width=688&height=252&name=Browser%20template%20(26).png)
2\. Click on** Resource ➞ Manage blends ➞ +Add a blend**
3\. One of your data sources will be added automatically, you have to join the data sources (tables) you want in the **Join another table** button.
-Jun-10-2024-10-28-12-9465-AM.png?width=688&height=252&name=Browser%20template%20(2)-Jun-10-2024-10-28-12-9465-AM.png)
4\. Now that you've 2 or more tables in the blend data option, **select the dimensions and metrics you want** to join on each data source.
-Jun-10-2024-10-30-28-1240-AM.png?width=688&height=252&name=Browser%20template%20(3)-Jun-10-2024-10-30-28-1240-AM.png)
5\. Now, let's click on "**Configure join"** to configure the relationship between each of the data sources you've added.
-Jun-10-2024-10-31-35-1872-AM.png?width=688&height=252&name=Browser%20template%20(4)-Jun-10-2024-10-31-35-1872-AM.png)
6\. There are 5 types of join operators: **left outer, right outer, inner, full outer, and cross.** Click [here](https://support.google.com/looker-studio/answer/9061420?hl=en) to see in-depth how each one works.
-Jun-10-2024-10-33-04-1367-AM.png?width=688&height=252&name=Browser%20template%20(5)-Jun-10-2024-10-33-04-1367-AM.png)
7\. We are going to select **Inner** as our join operator, as we want only the common data between both connectors. **Add** **the join conditions** you want.
-Jun-10-2024-10-36-29-2752-AM.png?width=688&height=252&name=Browser%20template%20(7)-Jun-10-2024-10-36-29-2752-AM.png)
8\. Give a name to the new blended data source and **save** the changes.
-Jun-10-2024-10-52-46-9507-AM.png?width=688&height=252&name=Browser%20template%20(8)-Jun-10-2024-10-52-46-9507-AM.png)
### Configuring our dashboard with the new blended data connector
1\. Add a chart and configure the table by adding **Date, Impressions (Table 1), and Impressions (Table 2).**
-Jun-11-2024-08-15-17-1132-AM.png?width=688&height=252&name=Browser%20template%20(9)-Jun-11-2024-08-15-17-1132-AM.png)
2\. Click on **Add metric** on the right sidebar and then click on **Create field**.
3\. Create a new **Total impressions **metric, which sums both impressions of both data sources. Both formulas below are valid:
``
```
IFNULL(Impressions (Table 1), 0) + IFNULL(Impressions (Table 2), 0)Impressions (Table 1) + Impressions (Table 2)
```
-Jun-11-2024-08-24-41-8744-AM.png?width=688&height=252&name=Browser%20template%20(2)-Jun-11-2024-08-24-41-8744-AM.png)
-Jun-11-2024-08-30-09-3649-AM.png?width=688&height=252&name=Browser%20template%20(3)-Jun-11-2024-08-30-09-3649-AM.png)
> ### Limitations and things to take into account about data blending
**The data blending option is an advanced option that requires a minimum knowledge of SQL Syntax.**
**You may have to use these functions to see the data the way you need:**
``
```
IFNULL()CONCAT()REGEXP_EXTRACT()REGEXP_REPLACE()REGEXP_MATCH()REGEXP_CONTAINS()
```
**The data blending option ONLY makes sense when we add common parameters in all the data sources.**
For example, if we add **Campaign** from Google Ads and **Campaign name** from Facebook, we can be in one of these three situations:
1\. The campaign names are different ➞ The blend data with Campaign does not make sense in this case.
2\. The campaign names are similar but not the same ➞ You may have to use a REGEXP\_EXTRACT() function to solve this and see both campaign names correctly.
3\. The campaign names are exactly the same ➞ You should see everything correctly.
[Read this article](https://dataslayer.ai/blog/limitations-of-data-blending-in-google-data-studio) to see in-depth some limitations the data blending has.
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