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Table of contents
Joins in Tableau
Blending in Tableau
Key Differences Between Joins and Blends
When to Use Joins vs. Blends in Tableau?
When to Use Joins
When to Use Blends
Examples of Joins and Blends in Practice
Frequently Asked Questions
Does Blending support all the operations that Join does?
Are there any performance considerations when choosing between Join and Blending?
Can I use Join and Blend?
What are the limitations of blends vs. joins?
Last Updated: Mar 27, 2024

Difference between Join and Blending in Tableau

Author Arya Singh
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Understanding joins and blends in Tableau is crucial for creating effective data visualizations that provide meaningful insights. Both functions serve different purposes, and understanding their fundamentals is essential for confidently using them in Tableau dashboards and reports.

This article will discuss the difference between them joins and blending in tableau, how to use and when to use those joins and Blends in data with examples.

Joins in Tableau

A join combines data at the row level, linking rows with a common field. There are a few types of joins:

  • Inner Join: Only includes rows that match in both tables. This is the default join type.
  • Left Join: Includes all rows in the left table and any rows in the right table that match. Rows in the right table without a match will have null values.
  • Right Join: The opposite of a left join. Includes all rows in the right table and any rows in the left table that match.
  • Full Outer Join: Includes all rows in both tables, matching rows where possible. Unmatched rows will have null values.

To perform a join, you must have a common field called the join key between tables. Drag tables onto the canvas, then right-click and select "Join..." to choose a join type and join key.

Joins are helpful when you have a direct relationship between tables based on values uniquely identifying each row. However, joins require that you have a standard join key, and they produce a static, flat table as output. If you need to combine data more flexibly, you'll want to use data blending.

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Blending in Tableau

Blending in Tableau allows you to combine data from multiple data sources into a single view, even when those data sources don’t have a direct relationship. This means you can create powerful visualizations that provide insights across your organization.

Blending in Tableau matches dimensions (like dates, locations, products, etc.) with the same or similar names. For example, if you have one dataset with “Product Category” and another with “Product Type”, Tableau will automatically blend them.

You can blend data at the data source, connection, or individual worksheet level. Blending at a higher level means the blended fields will be available to reuse in multiple views.

Simply drag sheets from different data sources onto the same worksheet to blend data. Tableau will automatically blend the data and show the combined results. You can then adjust the blend by:

  1. Removing or re-adding dimensions to control which fields are blended.
  2. Setting the blend type to control how dimensions are matched. For example, set to “Left” to prioritize all fields in the primary data source.
  3. Manually mapping dimensions that don’t automatically match. For example, map “Product Category” to “Product Type”.
  4. Adding a join clause to filter the data is blended. For example, join the datasets only for the “East” region.

Using data blending, you can gain valuable insights into your data that would otherwise require complex SQL joins and unions. Give blending a try—you'll be amazed at the hidden insights you uncover!

Key Differences Between Joins and Blends

The critical differences between joins and blends in Tableau are

Feature Joins Blends
Data sources Can combine data from two different sources Can only combine data from two worksheets within the same data source
Relationships Requires a relationship to be specified between the two data sources Relationships are automatically detected between columns with the same name and data type
Modifications Changes made to a joined data source will not automatically update in your Tableau workbook Changes made to a blended data source are automatically reflected in your workbook
Performance Typically provides faster performance since the data is physically combined into a single source Can be slower for workbooks with many complex blends

...It canThe main distinctions are the data source type, how relationships are established, whether changes are automatically updated, and performance impacts. Joins and blends each have their place in Tableau, so understanding how they differ will help you choose the right approach for your analysis. Knowing when to blend and when to join becomes second nature with practice.

When to Use Joins vs. Blends in Tableau?

Joins and blends are two of the most valuable tools in Tableau for combining data from multiple sources. However, it’s essential to understand the differences and when to use each one.

When to Use Joins vs. Blends in Tableau?

When to Use Joins

A join will combine data from two sources based on a common field. The data remains separate but linked, so you can still see what values came from which table. Use a join when:

  • You want to connect data with a one-to-one relationship. For example, joining an Orders table to a Customers table using Customer ID.
  • You need to preserve the original data sources. The data is linked but not blended into a single source.
  • There are duplicate values in the common field. A join will show rows for every match.

When to Use Blends

A blend merges the data from two sources into a single view. The data appears as if from one source. Use a blend when:

  • You want to combine measures or dimensions with the same meaning but different names in each table. Blending will "blend" them together into a single element.
  • There are no duplicate values in the standard fields. Blending duplicates would skew your results.
  • You need to hide the original data sources from view. The blended data will appear as a single dataset.

Ultimately, whether to use a join or a blend depends on how you need to see and interact with your data. Joins link data but keep it separate while blends fully combine data into a single view. By understanding how each works in Tableau, you can choose the right tool for the job and gain valuable insights into your data.

Examples of Joins and Blends in Practice

Joins and blends are two of the most valuable features in Tableau for combining data from multiple sources. While they may seem similar, there are some key differences to understand.


A join combines data from two tables by matching values in a common field. The data from the two tables is merged into a single table that contains all the fields from both tables.

For example, you have a customer table with contact details and a sales table with transaction information. You can join the two tables on the customer ID field to get a combined table with customer contact details and transaction history.

Joins can be inner joins, left joins, right joins, or full outer joins, depending on which rows you want to include from each table. Inner joins, the default join type, only include rows that match in both tables. The other join types include unmatched rows from one or both tables.


Unlike joins, blends do not combine the data from multiple tables into a single table. Blends link tables together visually, allowing you to see the combined data in views and dashboards, but the data is not merged at the row level.

For example, you have a transaction sales table and a date table with one row per day. You can blend the tables on the date field to create a view that shows sales figures for each day, with the day of the week's name coming from the dates table. However, the dates table is not part of the view’s data - it is just used to enhance the visualization.

Blends are best used to combine data just for visualization, not analysis. They provide a more flexible way to use lookup data to augment your views without modifying the underlying data.

The main differences to remember are that joins physically combine data at the row level, whereas blends link data visually for display purposes. Both are extremely useful for gaining insights from multiple related data sources in Tableau.

Frequently Asked Questions

Does Blending support all the operations that Join does?

While Blending offers some functionalities like filtering and aggregation, it may provide a different control over data than Joins. Complex calculations and interactions might be better suited for Joins.

Are there any performance considerations when choosing between Join and Blending?

Joins perform better for large datasets within a single source, as the database engine optimizes them. Blending might introduce additional overhead due to the need to fetch and match data from separate sources.

Can I use Join and Blend?

Yes, you can use Join and Blend in a Tableau workbook. For example, you may Join two data sources with a one-to-one relationship, then Blend in a third data source to add additional context. The order in which you add the data sources matters, so be sure to add the primary data source first, then Join and Blend in the additional sources.

What are the limitations of blends vs. joins?

Blends have limitations: sorting/filtering is per-source, calculations can't span blends, impacting performance due to querying multiple sources. Joins query one source, but blends need shared fields. Joins combine sources without needing standard fields.


The key is understanding how your data is structured and what you're trying to achieve. Determining when to join vs. blend in Tableau will become second nature with practice. Now get out there and start exploring your data - endless possibilities!

We hope this blog has helped you understand the difference between Join and Blending in Tableau. If you want to learn more, then check out our articles.

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