Data Relationship Vs Data Joining Vs Data Blending In Tableau

Handle multiple tables or data sources in Tableau!

Data Relationship, Data Joining, and Data Blending are three important concepts in Tableau that are essential for effective data analysis and visualization. In this blog, we will explore these concepts and how & when they are used in Tableau.

Let’s unfold the basics

Data Relationship

Data Relationship in Tableau refers to the way multiple tables or data sources are connected to create a single view. This connection is based on a common field or key in both tables, which is used to join them together. Tableau allows users to create a data relationship between tables, without the need to join them. We can use Data relationships to build more complex data models, especially when working with large data sets.

Data Joining

This refers to the process of combining two or more tables based on a common field or key to create a single, unified table. The purpose of joining data is to create a more comprehensive view of the data that includes information from both tables. Tableau supports different types of joins, including inner join, left join, right join, and full outer join, which allow users to customize how the tables are combined.

Data Blending

Data Blending is the process of combining data from multiple sources that are stored in different databases or file formats. In Tableau, data blending is used when a user wants to analyze data that is stored in different data sources or when a user wants to combine data from different levels of aggregation. The blending process involves creating a data connection between the data sources and then combining the data by matching the fields that are used to blend the data.

How they evolved

It’s worth noting that while Data Joining has been a part of Tableau since the beginning, it has evolved to include more advanced join types and options for customizing joins. However, Data Blending was a major addition to Tableau in version 6.0. It has continued to evolve and improve with subsequent releases.

Data Relationships are a more recent addition to Tableau. However, they have quickly become an important feature for working with multiple data sources and creating more complex data models.

It seems like every time we turn around, there’s a new concept to learn. As soon as we think we’ve got it, another one pops up to confuse us more. For example, think about Data Relationship, Data Joining, and Data Blending.

About Data Relationship, Data Joining and Data Blending

These three concepts are all about bringing different data sources together to create a more comprehensive view of the data. But let’s be real – who can keep them straight?

Data Joining is like trying to merge two puzzle pieces together – sometimes it works seamlessly, and other times you’re left with a big mess. Data Blending, on the other hand, is like trying to mix two different types of liquor – it might seem like a good idea at first, but the result is often a headache.

And as for Data Relationships, well, that’s like trying to navigate a complicated relationship with your ex. Sometimes it’s smooth sailing, other times it’s a total disaster, and most of the time you’re just left scratching your head and wondering why you ever got involved in the first place.

So if you’re still confused about Data Relationship, Data Joining, and Data Blending, don’t worry – you’re not alone.

Compare Data Relationship, Data Joining, and Data Blending

S. No.Aspecta) Data Relationshipb) Data Joiningc) Data Blending


Helps to connect two or more independent tables (from the same or different data connections or sources) but does not provide the merged tablesIt Helps to merge the data from two or more tables into a single table (from the same or different data sources or connections) & provides the merged table alsoHelps to combine the data from different sources or connections without physically joining them.

Use Case

Relationships are the default method and we can use them in most instances, including across tables with different levels of detail.Joins combine tables by adding more columns of data across similar row structures.Blends, unlike relationships or joins, never combine the data directly. Instead, blends query each data source independently, aggregate the results to the appropriate level, and then present the results together visually in the view. Because of this, blends can handle different levels of detail and also work with published data sources.

Concept Launch Year



Relationships are a dynamic, flexible way to combine data from multiple tables for analysis.Joins are a more static way to combine data so not very flexible.Related fields vary sheet by sheet so can be customized on a sheet-by-sheet basis only. Hence it is not flexible at all.


You can’t create relationships between tables from published data sources.You can’t use a published data source in a join. Joins can cause data loss or duplication if tables are at different levels of detail, and joins must be established before analysis can begin.Blends don’t create a new, blended data source. Instead, they are simply creating blended visuals per sheet.

Join Type Planning Required


Matching Fields

Requires matching fieldsRequires common fieldsN/A

Join Types Supported

It is based on Cardinality (Joins are NA)Left, Right, Inner, Full Outer JoinsLeft Join

Effect on Calculated Fields

Calculations are easy & straightforward with Relationships.Easy & straightforward Calculations with Joins.Calculations are different and difficult with Blending.

Effect on Tableau Functioning

Relationships are not combining the data at all. They are just connecting the data.A join combines the data and then aggregates.A blend aggregates and then combines the data.


To sum up, We hope we were able to give you better clarity w.r.t. when & how to use which one. Give it a practical try & if unable to do then connect with us. We would be happy to assist you. Happy Learning!

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