If you’re a Google Data Studio advanced user, I'm sure you’ve already used the data blending feature.

What data blending is

Blending data lets you create charts, tables, and controls based on multiple data sources in the same dashboard.


How blend works step by step

Creating a new blended connector
If you already know how to create a blended connector you can skip these steps.

Make sure you have 2 or more active connectors on your Google Data Studio dashboard.


Click on ResourceManage blends+Add a blend


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.


Now that you've the 2 or more tables in the blend data option, select the dimensions and metrics you want to join on each data source.


Now, let's click on Configure join to configure the relationship between each of the data sources you've added.


There are 5 types of join operators: left outer, right outer, inner, full outer and cross. Click here to see in depth how each one works.


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.


Give a name to the new blended data source and save the changes.


Configuring our dashboard with the new blended data connector

Add a chart and configure the table adding Date, Impressions (Table 1) and Impressions (Table 2).


Click on Add metric on the right sidebar and then click on Create field.


Create a new Total impressions metric, which sum 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)




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:

The campaign names are different ➞ The blend data with Campaign does not make sense in this case.
The campaign names are similar but not the same ➞ You may have to use a REGEXP_EXTRACT() function to solve this and see correctly both campaign names.
The campaign names are exactly the same ➞ You should see everything correctly.

Read this article to see in-depth some limitations the data blending has.

If you still have doubts or questions please contact us via our live chat on our website or via email.
Was this article helpful?
Cancel
Thank you!