What is Blending in Tableau?

Bringing data from different places together is often the first, and most frustrating, step in data analysis. Tableau's data blending feature is designed to solve this exact problem, allowing you to combine disparate data sources, like a SQL database and a Google Sheet, directly within a dashboard. This article breaks down what data blending is, how it differs from joining, and provides a step-by-step guide to get you started.

What is Data Blending in Tableau?

Data blending is a method for combining data from multiple, different data sources in a single Tableau view. Think of it as a smart way to display summary numbers from separate reports side-by-side. Instead of merging all the raw data into one big table beforehand, blending queries each data source independently, aggregates the results, and then visually brings those aggregated results together based on a common field.

A simple analogy is planning a big party. You have a list of RSVPs in an Excel file (Data Source 1) and a list of all your professional contacts in Salesforce (Data Source 2). Data blending is like putting both lists next to each other and using the "Name" column to see which professional contacts have RSVP'd, without having to first merge both lists into a single master spreadsheet.

In technical terms, data blending functions like a post-aggregate left join. This means it gathers the summarized data first and then stitches it together. This approach is powerful because it lets you work with data sources that can't be joined easily, like data from Google Analytics and your internal SQL warehouse.

Data Blending vs. Joining: What's the Key Difference?

If you've spent any time with data, you've likely heard of "joining." While both joining and blending combine data, they work in fundamentally different ways, and choosing the right one is crucial for getting accurate results.

Joining combines tables at the row level. It creates a new, wider table in your data source by matching rows based on a common field. This happens before any aggregation or visualization. You typically use joins when your data lives within the same source, such as combining two tables within a single SQL database.

Blending, on the other hand, works with aggregated data at the worksheet level. It doesn't create a new, combined table. Instead, it sends separate queries to each data source, gets summarized results back, and then mixes those results in your view. It's the go-to method for combining data from completely different systems.

Here’s a quick breakdown to help you decide which to use:

When to Use Joining:

• Your data is in the same database or file (e.g., combining two tables from a PostgreSQL database or two sheets within the same Excel workbook).
• You need to combine data at a granular, row-by-row level before visualizing.
• You need a new, permanent combined table of data that can be used across multiple analyses.

When to Use Blending:

• Your data is in completely different sources (e.g., Salesforce, Google Sheets, and a Snowflake database).
• You want to combine data at an aggregated level (like displaying total sales from an SQL database next to monthly sales targets from a spreadsheet).
• You want a quick way to combine data without extensive data pipeline work or creating a new table upfront.

A simple rule of thumb: If you can join your data, you probably should, as it's often more performant. If you can't because the data lives in separate systems, blending is your answer.

How Does Data Blending Work?

Understanding blending requires knowing two key concepts: primary and secondary data sources, and linking fields.

Primary vs. Secondary Data Sources

When you blend data, Tableau designates one data source as "primary" and the other(s) as "secondary."

• Primary Data Source: This is the first data source you bring a field from into your view. The dimensions and measures you drag into your worksheet from this source will appear as blue "pills." This source sets the base level of detail for your visualization. All data from the primary source will be included in the view.
• Secondary Data Source: Any subsequent data source you use in the same worksheet becomes a secondary source. The pills from this source will appear orange. Tableau will only bring in data from secondary sources where the values in the "linking field" match a value in the primary source.

This primary/secondary relationship is why blending is often compared to a left join - it starts with everything from the left table (primary source) and pulls in matching data from the right table (secondary source).

Linking Fields

The "linking field" is the common dimension that connects your primary and secondary data sources. For blending to work, you need at least one field that exists in both sources, like a "Date," "Region Name," or "Customer ID."

In the Data pane, Tableau automatically identifies potential linking fields and shows an active link (an unbroken gray chain icon) next to the field name. If you want to use a different field to link the sources, you can click the broken chain icon next to it to make it active. This tells Tableau exactly how to match the aggregated data from one source to the other.

A Step-by-Step Guide to Data Blending in Tableau

Let's walk through a realistic scenario. Imagine you're a marketing manager, and you have sales figures in a SQL database, but your quarterly sales targets are stored in a simple Google Sheet. You want to build a quick view to see how each region is performing against its target.

Your Data Sources:

• Source 1 (SQL Database): A table called Sales_Actuals with columns like Region, Sale_Date, and Revenue.
• Source 2 (Google Sheet): A sheet called Sales_Goals with columns Region and Quarterly_Goal.

Step 1: Connect to Your Data Sources

First, you need to connect both data sources in your Tableau workbook.

1. Open Tableau and connect to your SQL Database. Load the Sales_Actuals table.
2. Next, click the "Add" button next to "Data Sources" in the data pane, or select Data > New Data Source.
3. Select "Google Sheets" and connect to your Sales_Goals sheet.

You should now see both data sources listed in your Data pane.

Step 2: Establish the Primary Data Source

For this analysis, we want to see all our actual sales data, regardless of whether a goal exists. So we'll make our Sales_Actuals the primary source.

To do this, simply select the Sales_Actuals source in the Data pane and drag the Region dimension onto the Rows shelf. Because this is the first field in the view, Sales_Actuals is automatically set as the primary source, and the "Region" pill will be blue.

Step 3: Define the Linking Field

Now, click on your second data source, Sales_Goals, in the Data pane. You'll notice that Tableau has likely identified Region as a common field and is displaying a small, unbroken chain link icon next to it. This indicates it is the active linking field. If another field was incorrectly linked, you could click the chain icon next to it to break the link and click the icon next to Region to activate it.

Step 4: Bring in Data from the Secondary Source

With the primary source and linking field established, you can now bring in data from your secondary source. From the Sales_Goals data source, drag the Quarterly_Goal measure over to the Columns shelf. You'll notice this pill is orange, indicating it comes from a secondary source. Tableau now displays the goal for each corresponding region from your primary source.

Step 5: Complete Your Visualization

To finish the view, go back to your primary Sales_Actuals data source and drag the Revenue measure onto the Columns shelf. You can now create a combination chart - perhaps a bar chart for actual revenue and a Gantt line for the goal - to easily compare performance for each region. You've successfully blended data from a SQL database and a Google Sheet!

Common Blending Issues & Best Practices

While powerful, blending has some quirks. Here are a few things to watch out for.

Handling Asterisks (*)

Sometimes, after blending, you might see an asterisk (*) in your view where you expect a value. This usually happens when a single value in your primary source matches multiple values in your secondary source. For example, if your primary source has one row for "USA" and your secondary has multiple rows for "USA" (perhaps one for each state), Tableau doesn't know which of the multiple secondary values to display, so it shows an asterisk.

The Fix: The best solution is to ensure your linking fields create a one-to-one relationship relevant to your view. You might need to adjust the level of detail (granularity) in your worksheet by adding more specific dimensions.

Filtering Limitations

Filters in blending work a bit differently. A filter applied to a field from the primary source can affect data from both sources. However, a filter on a field from the secondary source will only filter data from that secondary source.

Best Practices to Keep in Mind:

• Start with the more granular source as primary. If one data source has daily dates and the other has monthly dates, use the one with daily dates as your primary. This ensures you aren't missing any potential matches.
• Clean up your linking fields. Ensure the values match exactly. "Los Angeles" in one source and "L.A" in the other won't link properly.
• Only link what's necessary. Deactivate links for fields you don't need to blend. Leaving an active link on a 'Date' field when you only intend to link by 'Region' can sometimes produce unexpected results.

Final Thoughts

Data blending in Tableau is a flexible and essential feature for any analyst who needs to synthesize information from various systems quickly. While joins are better for same-source, row-level combinations, blending excels at aggregating and comparing data living in different platforms without writing complex code or building data pipelines.

Manually connecting multiple sources and building visualizations is powerful, but often it's still more work than necessary, especially for sales and marketing teams who need answers fast. We created Graphed to automate this entire process. Instead of setting up data blending in Tableau, you can connect your Salesforce, Google Ads, and Shopify data with just a few clicks, then ask in plain English: "Show me my Facebook Ad lead count vs my Salesforce opportunities created last month." Graphed instantly builds a live dashboard, letting you get insights without the setup.