Data Studio Introduces New Data Blending Options — a Game Changer for Data Visualisation

4 new data blending options remove one of the biggest limitations of the platform

In March 2021, I wrote about my biggest pet peeves with Google Data Studio — amongst which was the inability to blend two tables in a way different than left outer join.

Today, Google Data Studio released an update, which allows for four additional join types of tables, including Inner Join, Left outer join, Right outer join, Full outer join, and Cross join.

Let’s discuss this update and the implications it may have on data visualization in Data Studio.

Data Blending Gets an Update — Introducing New Join Types

Blending Data in Google Data Studio is used to follow SQL parameters for Left Outer join.

On the 17th of February, Google Announced new ways of blending data, including Inner Join, Left outer join, Right outer join, Full outer join, and Cross join.

Left outer joins work by blending data by taking all the records from the left data source and combining them with the matching records from the right data source.

Left outer join — Image by Google (archived)

What did having only left outer join mean in practice?

When using left outer joining, you have to pay extra special attention to how your two data sources are blended, and more specifically, the order in which you add them to the blended data entity.

Based on the definition of a left outer join, the first table (data source) added will be the one that will be used as a basis, so any additional data entries from the second one (that go beyond the join key field from the first table) will not be admitted into the new dataset.

This is a very limiting approach to joining tables as although it is advanced enough to seek patterns, it is rejecting null values.

How many join types are there in total?

In total, there are 7 types of table joins, which data science professionals are used to working with. Having only one can feel quite…