Data blending in Looker Studio (formerly Data Studio) is a feature offered by the platform to cross-reference data from two different data sources. It works very similarly to an Excel pivot table, as it uses an identical dimension from the data sources and very useful tables, graphs and boards can be prepared for the creation of a professional dashboard.
Thanks to this function we can merge data from tables in Google Sheets, Google Ads, Google Analytics 4, Facebook Ads and all kinds of resources. The only condition is that the dimension has exactly the same name.
Merge data with right click
The best way is to create two identical charts with different data singapore whatsapp number sources, then select these two charts, right-click and at the bottom you will see 'Blend data'. From experience, this is the ideal way to do it.
In the following video, we use two time charts with different data sources and metrics that have nothing to do with each other. But it can also be done with tables, which is very interesting to see the data side by side and even create new fields that compare both metrics.
Video player
00:00
00:47
Combine data sources from scratch
In the top bar of Looker Studio, select 'Resources', then 'Manage combinations' and then create a new data combination. A new window will open, where you can edit this combination.
On the one hand we see Table 1, which we can name, and here we will select the data source. Then we choose the dimension that matches both data sources, and we add the metrics that we are interested in seeing. We do the same with the second data source and we are almost done.
In the following image, we are interested in crossing data from Google Sheets (Excel) with the data provided by Google Analytics. For example, something as common as a budget and data: Sessions, Users, Conversions, etc.
Merge data in looker studio
Setting up the union between data sources
To finish preparing this data combination, we need to configure the relationship between the data sources.
Left Outer and Right Outer are the most common. As the definition says, it returns all the rows from the source that match in the right table and those that do not match in the left table.
Inner will only show the data that matches both dimensions. For example, if we have 'Months' as the dimension, only the months for which there is data in both data sources will appear.
Full Outer returns all rows from both data sources, whether they match or not.
Cross Join is really useful for combining data between scorecards. Select both, right click and merge data. You will see a division of one by the other and you will be able to get conversion rates, ratios and percentages.