May 18th, 2023
Tableau Relationships vs. Joins: When to Choose What?
Data is the foundation of every successful business. With the rise of big data, it’s essential to use the right tools to organize, analyze and visualize information. Tableau is one of the most popular and powerful tools. It enables users to connect, blend and visualize different data sources easily.
When it comes to joining data, Tableau offers two distinct methods: Relationships and Joins. Both approaches serve the same purpose; however, they differ in handling data connections.
In this blog, we’ll explore the differences between Tableau Relationships and Joins, and help you determine when to choose what.
What is Tableau Relationships?
Tableau relationships simplify the process of connecting and analyzing data by allowing users to leverage the natural hierarchies within their data. This means that users can define common fields or data organization, and Tableau will automatically create the necessary connections in its data model.
Tableau relationships are a preferred way of connecting different data tables as they can automatically handle changes in the underlying data structure.
Types of Tableau Relationships
Tableau supports three types of relationships between data tables. The choice of a relationship depends on the underlying organization of data. These relationships are:
1. One-to-one Relationship
In a one-to-one relationship, each record in one table(primary table) is linked to a single record in another table(secondary table). This relationship is useful when there is a unique relationship between the tables.
The figure below illustrates a unique relationship between the OrderPrice and OrderDetails tables. Both tables are uniquely related to each other on the Order ID column.
2. One-to-many Relationship
In a one-to-many relationship, each record in one table(primary table) can be linked to multiple records in another table(secondary table). This relationship is useful when one table contains a list of unique entities (e.g., customers), and the other table contains multiple records for each entity (e.g., orders).
The diagram below illustrates a one-to-many relationship between the Customers and Orders tables. The Customers table is unique for every customer, whereas the Orders table can have repeated rows as each customer can buy many products at the same. Each row in the Customers table can be linked to multiple tables in the Orders table.
3. Many-to-many Relationship
In a many-to-many relationship, each record in one table can be related to many records in another and vice versa.
The tables below are related in a many-to-many relationship because each order can contain multiple products, and each product can be included in multiple orders.
Steps to Manage Tableau Relationships
Tableau relationships simplify the process of connecting data tables. When you import a dataset in Tableau, it will automatically find the best relationship between your data tables. Tableau also allows you to change the relationships between two tables.
The steps below demonstrate changing the type of relationship between two data tables. To follow along with this demonstration, download the dataset by clicking here. After downloading, import the dataset into Tableau.
- Drag and drop the Customers and Orders table into Tableau’s data modeling pane. Tableau will establish a relationship between the tables based on the underlying data structure.
To know the type of relationship that Tableau established between the two tables, hover over the line connecting the two tables.
The image above shows a many-to-many relationship between the Customers and Orders tables.
- To change the type of relationship between the two tables, click on Performance Options.
- Under the Performace Options, you can specify the relationship you want to establish between your tables.
It is extremely important to understand your data structure before making changes to the type of relationship. This is because Tableau relationships are designed to establish a connection between the data tables that is the most efficient.
What are Tableau Joins?
Tableau joins creates a unified data source from multiple data tables. It does so by linking common fields in two or more tables.
Types of Tableau Joins
The following are the types of joins in Tableau:
Inner Join
Inner join returns only the matching rows between the two tables. Any non-matching rows are excluded.
Demonstration of Inner Join:
To follow along with this demonstration, download the dataset by clicking here. After you download the files, the two data tables on which we’ll perform joins will have the following tables:
- Customers table
- Orders Table
To perform an inner join in Tableau, import the excel file you downloaded. Drag and drop the Customers and Orders table to the modeling pane. By default, Tableau will perform an inner join.
When we perform an inner join on our Customers and Orders table, it returns the following table:
The table shows that only matching rows between Orders and Customers tables are returned.
Left Join
Left join returns all the rows from the left table and matching rows from the right table. Any non-matching rows from the right table will have null values.
Demonstration of Left Join
To change the type of join from an inner join to a left join, double-click on the two circles and select Left.
The table below shows that left join returns all the rows from the Customers table(or left table) and only matching rows from the Orders table(or right table).
Right Join
Right join returns all the rows from the right table and matching rows from the left table. Any non-matching rows from the left table will have null values.
Demonstration of Right Join
To change the type of join, double-click on the two circles and select Right.
The table below shows that all the rows from the Orders table and only matching rows from the Customers table are returned.
Full Outer Join
Full outer join returns all the rows from both tables, whether or not there is a match in the other table.
Demonstration of Full Outer Join
To change the type of join, double-click on the two circles and select Full Outer.
Full outer join returns all the rows from both tables as shown below:
When to Choose Relationships?
Following are some scenarios where one would prefer using relationships over joins:
Small datasets with a clear relationship
Use Tableau relationships when you have a small dataset with a clear relationship between tables. This is because relationships are more flexible to changes in the data structure and make it easier to navigate the data.
When performance is a concern
Performance can sometimes be a critical factor in the analysis. Relationships can improve performance by reducing the number of tables that need to be joined. Furthermore, relationships give Tableau the freedom to optimize queries.
Benefits of using relationships in Tableau
There are several benefits to using relationships in Tableau, some of which are:
Ease of use and maintenance
Relationships are simpler and allow you to create a more simplified data model in Tableau. This makes understanding and maintaining the data source easier and allows for more accessibility across data teams.
Improved data accuracy and consistency
Relationships can ensure data accuracy and consistency by avoiding the creation of duplicate data. This can help prevent inconsistencies when data is replicated across multiple tables.
When to Choose Joins?
Following are some scenarios where one would prefer using joins over relationships:
Combining multiple datasets with different keys
Joins can help create a unified view of the data. If you have multiple datasets with different keys, using joins may be necessary to combine them. This is especially useful when dealing with data sources that have complex structures.
Merging tables with different structures
Joins allow you to merge data from tables with different underlying structures. With joins, you can create a more customized view of the data, allowing you to manipulate and analyze it in different ways.
Benefits of using joins in Tableau
Following are some of the benefits of using joins in Tableau:
Flexibility and control over the merged data
Joins give you more control over how the data is merged and how the final output is structured. This is useful when dealing with complex data sources or creating a custom data view.
Ability to merge data from different sources
Joins allows one to merge data from different sources, such as databases, spreadsheets, or cloud data sources. This is useful when analyzing the current state of the entire business’s processes.
The table below summarizes all the main points discussed above and will act as a helping summary in choosing when to use Tableau relationships and joins.
| Evaluation factor | Relationships | Joins |
| Datasets | If the dataset is small and has a clear relationship | If multiple datasets with different keys need to be combined |
| Relationship | If there is a clear relationship between tables | If tables have different structures |
| Data Model | If performance is a concern and a simpler data model is needed | If a more customized view of the data is required |
| Data accuracy/consistency | If avoiding duplicate data is important | If a more comprehensive view of the data is needed |
