Tableau Lesson 13 – Data Blending | Dataplexa

Section II — Lesson 13

Data Blending in Tableau

Data blending lets you combine data from two completely separate sources — such as an Excel file and a Google Sheets document — in the same view, even when a direct join or relationship is not possible.

What Data Blending Is

A data blend is not a join. Joins and Relationships physically or logically combine tables that share the same connection. Data blending works differently — it queries two separate data sources independently, aggregates each result, and then combines those aggregates in the view at the worksheet level.

The most common scenario for blending is when your primary data lives in one system — say a company database — and supplementary data lives in another — say a regional target spreadsheet sent by the finance team. You cannot join them because they are in different systems. Data blending lets you bring them together in Tableau without moving the data.

Primary vs Secondary Source

In any blend, one data source is the primary and the other is the secondary. This distinction matters because blending is not symmetrical — the two sources are treated very differently.

Primary Source

•The source you connect to first and use most of your fields from

•Dimensions from the primary drive the view — they appear as blue pills

•Whichever source is used first in a worksheet automatically becomes primary

Secondary Source

•The supplementary source that contributes additional measures to the view

•Fields from the secondary appear with an orange chain-link icon in the Data pane

•Secondary data is always aggregated before being combined — you cannot use row-level secondary fields

The Blend Link Field

For a blend to work, both sources must share at least one common Dimension — a field with matching values in both. This is the blend link field. For example, if both sources contain a Region column with the same four values (East, West, Central, South), Tableau can align the two sources on Region.

Tableau usually detects the link field automatically when field names match exactly. You can see and manage link fields in the Data pane — they appear as an orange chain-link icon next to the field name in the secondary source. Clicking the icon toggles the link on or off.

Data Pane — Blend Active

Primary — Superstore (Excel)

Abc Category

🔗 Abc Region LINKED

# Sales

Secondary — Targets (Google Sheets)

🔗 Abc Region LINKED

# Sales Target

Setting Up a Blend — Step by Step

The goal here is to blend Superstore Sales data with a separate regional Sales Targets spreadsheet, so you can compare actual Sales vs Target by Region in the same chart.

Connect to your first data source — the Superstore Excel file. This becomes the primary source. Build a basic view by dragging Region to Columns and Sales to Rows.

Go to Data → New Data Source and connect to the second source — the Sales Targets spreadsheet. This creates a second data source in your workbook but does not replace the first.

Return to your worksheet. In the Data pane, you now see both sources listed. Tableau detects that both have a Region field and automatically shows the orange chain-link icon next to Region in the secondary source — confirming the blend link is active.

From the secondary source, drag Sales Target onto the Rows shelf alongside SUM(Sales). Tableau blends the two sources on Region and adds the Target bars to the view. Both measures now appear side by side per Region.

How Blending Aggregates Data

Understanding the aggregation behaviour of blending is critical — it is the most common source of incorrect numbers in a blended view. Here is exactly what happens under the hood:

Tableau queries the primary source and aggregates its measures at the level of detail defined by the Dimensions in the view — in this case, SUM(Sales) per Region.

Tableau separately queries the secondary source and aggregates its measures at the same level — SUM(Sales Target) per Region.

Tableau combines the two aggregated results by matching on the link field (Region). The final view shows both values side by side for each Region. There is no row-level combination — only aggregate-level combination.

Blending vs Joining vs Relationships

Method	Combines	Row-level access	Cross-source	Best for
Join	Tables in same source	Yes	No	Same-connection table merges
Relationship	Tables in same source	Yes	No	Same-connection multi-table analysis
Data Blend	Separate data sources	No — aggregates only	Yes	Combining data that cannot be joined

Common Blending Problems

Asterisk (*) values

The secondary source returns asterisks instead of numbers. This means the blend link field has more granularity in the secondary than the primary — Tableau cannot aggregate to a single value per Dimension member. Fix by adjusting the link field or aggregating the secondary data further.

No link detected

Tableau shows no chain-link icon and secondary fields are greyed out. This happens when the shared field has different names in each source. Fix by going to Data → Edit Blend Relationships and manually specifying which field in the primary maps to which field in the secondary.

Wrong aggregation

Secondary measures aggregate at a different grain than intended. Remember that the secondary is always queried at the level of detail of the primary's Dimensions in the view — if you change which Dimensions are in the view, the secondary aggregation changes too.

Editing Blend Relationships Manually

When Tableau cannot detect the link automatically — because field names differ — you configure it manually. Go to Data → Edit Blend Relationships. A dialog lists all data source pairs and lets you specify custom field mappings between them. For example, map "Region" in the primary to "Sales Region" in the secondary. Once saved, Tableau uses this mapping for all blended worksheets in the workbook.

📌 Teacher's Note

Data blending is one of Tableau's older features — it predates Relationships and was the original solution for cross-source analysis. It works well for its specific use case: bringing in a small supplementary aggregated dataset from another source. But it has real limitations. You cannot use row-level secondary fields, the asterisk problem catches many beginners off guard, and blends can be slow on large secondary sources. If you find yourself doing complex analysis that requires row-level data from both sources, the right answer is to combine those sources upstream — in a database, in Tableau Prep, or in Excel — and connect to the merged result as a single source. Use blending as a quick bridge, not a permanent architecture.

Practice Questions

1. In a data blend, which source automatically becomes the one whose Dimensions drive the view — determined by whichever source you use first in the worksheet?

2. When the link field has different names in two data sources, where do you go in Tableau to manually specify the field mapping for a blend?

3. What symbol does Tableau display instead of a number when the secondary source has more granularity than the primary and cannot aggregate to a single value per Dimension member?

Next up — Lesson 14: Relationships in Tableau — the modern way to combine tables that preserves each table's granularity and prevents row duplication.

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