Data Joining vs. Data Blending in Tableau: When and How to Use Each

If we working with data in Tableau, we often encounters the need to combine data from multiple sources or tables. Tableau offers two primary methods for combining data: Data Joining and Data Blending. While both techniques are used to bring data together, they serve different purposes and are suitable for different scenarios. Understanding when and how to use each method is crucial for efficient and accurate data analysis. This article explores the differences between Data Joining and Data Blending in Tableau, providing insights into their use cases and practical applications.

Data Joining

Data Joining is a method of combining data from two or more tables within the same data source based on a common field (key). This process happens at the database level, resulting in a single, combined data table.

Data Joins

How to Perform a Join in Tableau:

1. Connect to Data

Open Tableau and connect to your data source.

Connect to data

2. Drag Tables

Drag and open the tables you want to join into the data pane.

Drag and open the first table

Drag the other table

3. Define Join Condition

Select the common field(s) and specify the type of join (inner, left, right, or full outer).

Choose join condition

4. Preview and Adjust

Preview the joined data and make any necessary adjustments.

Types of Joins

• Inner Join: Returns only the rows with matching keys in both tables.

Inner Join

• Left Join: Returns all rows from the left table and matching rows from the right table.

Left Join

• Right Join: Returns all rows from the right table and matching rows from the left table.

Right Join

• Full Outer Join: Returns all rows when there is a match in either table.

Outer Join

Use Cases for Data Joining:

• Single Data Source: When data resides within a single source or database.
• Large, Complex Datasets: Suitable for combining large datasets where performance is crucial.
• Simple Relationships: Ideal for straightforward, direct relationships between tables.

The Pros and Cons of Using Data Joining in Tableau

Data Blending

Data Blending is a method of combining data from multiple sources in Tableau. This process occurs at the visualization level, allowing you to blend data from different databases or disparate sources.

How to Perform Data Blending in Tableau:

1. Connect to Primary Data Source

Open Tableau and connect to your primary data source.

Open and connect to data

2. Connect to Secondary Data Source

Add the secondary data source(s) by click the ‘New Data Source’

Add new data source

3. Create Relationships

Define the relationship between the primary and secondary data sources using a common field.

You can also edit the blend relationships.

Edit blend relationship

Edit data source field

Primary and Secondary Data Sources:

• Primary Data Source: The main data source for the visualization.
• Secondary Data Source: The additional data source(s) used for blending.

4. Linking the Data Sources

Before you link the data source, you can’t use both of the data in one sheet because there is no relationship to the primary data source and warning message will show.

Warning message

You can link the data source by clicking the chain beside the same column of both data

Linking process

After linking

5. Use Blended Data in Visualizations

Drag fields from both data sources into the worksheet. Tableau will automatically blend the data based on the defined relationship.

Visualizations from two data source

Use Cases for Data Blending:

• Multiple Data Sources: When data comes from different sources or databases.
• Aggregated Data: Suitable for blending aggregated data with detailed data.
• Complex Calculations: Ideal for performing calculations across different datasets.

The Pros and Cons of Using Data Blending in Tableau

Comparative Summary

Conclusion

Both Data Joining and Data Blending are essential techniques in Tableau, each with its own strengths and limitations. Data Joining is ideal for combining tables within a single data source, providing efficiency and simplicity. On the other hand, Data Blending offers flexibility to merge data from multiple sources, making it suitable for more complex analytical scenarios. Understanding when and how to use each method will empower you to leverage Tableau’s full potential and derive more meaningful insights from your data.