Why Union and join basics in Tableau? - Purpose & Use Cases

The Big Idea

What if you could combine all your scattered data with just a few clicks, no copying needed?

The Scenario

Imagine you have sales data in two separate Excel files for different regions. You want to see all sales together and also compare customer details from another file. Doing this by copying and pasting data manually into one sheet is tiring and confusing.

The Problem

Manually combining data means lots of copying, pasting, and reformatting. It's easy to make mistakes like missing rows or mixing up columns. When data updates, you have to repeat the whole process, wasting time and risking errors.

The Solution

Using unions and joins in Tableau lets you combine data from multiple sources quickly and accurately. Unions stack data tables with the same columns, while joins merge tables based on matching fields. This keeps your data connected and up-to-date automatically.

Before vs After

✗ Before

Copy data from file A
Paste below data from file B
Manually match customer info

✓ After

Use UNION to stack tables
Use JOIN to merge on customer ID

What It Enables

You can easily create combined views and reports that update automatically when your data changes, saving hours of manual work.

Real Life Example

A retail manager combines online and in-store sales data to see total revenue and customer trends in one dashboard without juggling multiple spreadsheets.

Key Takeaways

Manual data merging is slow and error-prone.

Unions stack similar tables; joins merge related tables.

Tableau automates combining data for faster, accurate insights.

Practice

1. Which of the following best describes a Union in Tableau?

easy

A. It filters data based on a condition.

B. It combines columns from two tables based on matching keys.

C. It creates a new calculated field.

D. It stacks rows from two or more tables with similar columns.

Solution

1. Step 1: Understand Union purpose

   A Union stacks rows from tables that have the same columns, combining data vertically.

2. Step 2: Compare with Join

   Join combines columns horizontally based on matching keys, not stacking rows.

3. Final Answer:

   It stacks rows from two or more tables with similar columns. -> Option D

4. Quick Check:

   Union = stacking rows [OK]

Hint: Union stacks rows; Join combines columns [OK]

Common Mistakes:

• Confusing Union with Join
• Thinking Union combines columns
• Assuming Union filters data

2. Which syntax correctly represents a Join in Tableau's data source page?

easy

A. Drag one table onto another and select the join type.

B. Use the UNION keyword in the data pane.

C. Create a calculated field with JOIN() function.

D. Right-click a table and select 'Append'.

Solution

1. Step 1: Identify Join method in Tableau

   In Tableau, you join tables by dragging one table onto another and choosing the join type (Inner, Left, Right, Full).

2. Step 2: Eliminate incorrect options

   Union keyword is for unions, JOIN() function does not exist, and 'Append' is not a Tableau option.

3. Final Answer:

   Drag one table onto another and select the join type. -> Option A

4. Quick Check:

   Join = drag tables + select join [OK]

Hint: Join by dragging tables together in Tableau [OK]

Common Mistakes:

• Confusing Union keyword with Join
• Looking for JOIN() function which doesn't exist
• Using 'Append' instead of Union or Join

3. Given two tables:
Table A: ID, Name
Table B: ID, Sales
What will be the result of an Inner Join on ID?

medium

A. A table with only IDs from Table A and no Sales column.

B. A table stacking all rows from both tables vertically.

C. A table with columns ID, Name, Sales containing only matching IDs.

D. A table with all IDs from both tables, including unmatched rows.

Solution

1. Step 1: Understand Inner Join behavior

   Inner Join returns rows where the join key (ID) exists in both tables, combining columns.

2. Step 2: Analyze columns and rows

   The result will have columns ID, Name, Sales and only rows with matching IDs in both tables.

3. Final Answer:

   A table with columns ID, Name, Sales containing only matching IDs. -> Option C

4. Quick Check:

   Inner Join = matching rows + combined columns [OK]

Hint: Inner Join keeps only matching keys with all columns [OK]

Common Mistakes:

• Thinking Inner Join stacks rows
• Expecting unmatched rows included
• Confusing columns included in result

4. You tried to Union two tables but got an error. What is the most likely cause?

medium

A. You forgot to select a join type.

B. The tables have different column names or data types.

C. You used a calculated field instead of a table.

D. You dragged tables instead of using the Union option.

Solution

1. Step 1: Identify Union requirements

   Union requires tables to have matching column names and compatible data types to stack rows.

2. Step 2: Understand error cause

   If columns differ in name or type, Tableau cannot stack rows, causing an error.

3. Final Answer:

   The tables have different column names or data types. -> Option B

4. Quick Check:

   Union error = mismatched columns/types [OK]

Hint: Union needs matching columns and types [OK]

Common Mistakes:

• Confusing Union errors with Join errors
• Not checking column names and types
• Trying to drag tables instead of using Union

5. You have monthly sales data split into two tables: Sales_Jan and Sales_Feb with identical columns. You also have a Customers table with customer details. How do you create a combined dataset showing all sales with customer info?

hard

A. Union Sales_Jan and Sales_Feb, then Join the result with Customers on CustomerID.

B. Join Sales_Jan with Customers, then Union with Sales_Feb.

C. Union Customers with Sales_Jan and Sales_Feb directly.

D. Join Sales_Jan and Sales_Feb on CustomerID, then Union with Customers.

Solution

1. Step 1: Combine monthly sales data vertically

   Since Sales_Jan and Sales_Feb have identical columns, use Union to stack their rows into one sales table.

2. Step 2: Enrich sales data with customer info

   Join the combined sales table with Customers on CustomerID to add customer details horizontally.

3. Final Answer:

   Union Sales_Jan and Sales_Feb, then Join the result with Customers on CustomerID. -> Option A

4. Quick Check:

   Union sales first, then Join customers [OK]

Hint: Union similar tables first, then Join related tables [OK]

Common Mistakes:

• Joining before unioning sales tables
• Trying to union unrelated tables
• Joining sales tables instead of unioning