Union and join basics in Tableau - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding the difference between Union and Join

Which statement best describes the difference between a Union and a Join in Tableau?

A A Union combines tables horizontally by matching columns; a Join stacks tables vertically by adding rows.

B A Union stacks data tables vertically, adding rows; a Join combines tables horizontally, adding columns based on matching keys.

C Both Union and Join stack tables vertically but differ in how they handle duplicates.

D A Union merges tables by matching keys; a Join appends tables without matching.

💡 Hint

Think about whether you are adding rows or columns when combining tables.

In Tableau, a Union appends tables vertically, adding rows from each table. A Join combines tables horizontally by matching rows based on key columns, adding columns.

🧠 Conceptual

intermediate

Result of a Left Join in Tableau

Given two tables in Tableau: Customers with 5 rows and Orders with 10 rows, where 3 customers have orders, what is the number of rows after a Left Join of Customers to Orders?

A 5 rows

B 10 rows

C 15 rows

D 3 rows

💡 Hint

Remember, a Left Join keeps all rows from the left table.

A Left Join keeps all rows from the left table (Customers). Since Customers has 5 rows, the result will have 5 rows, with matching Orders data where available.

❓ visualization

advanced

Visualizing the effect of a Union

You have two tables with sales data for two different years. You perform a Union in Tableau. Which visualization best shows the combined sales over both years?

A A bar chart comparing sales side by side for each year without combining data.

B A pie chart showing sales distribution by year separately.

C A line chart showing sales over time with data points from both years combined.

D A scatter plot showing sales vs. customers for only one year.

💡 Hint

Think about how a Union stacks data and how to show combined trends.

A Union stacks data vertically, so combining sales from both years allows a line chart over time to show the total sales trend across years.

🔧 Formula Fix

advanced

Troubleshooting a Join with Missing Data

You performed an Inner Join between Products and Sales tables on Product ID, but some expected products are missing in the result. What is the most likely cause?

A Some Product IDs in Products do not match any Product ID in Sales, so those rows are excluded.

B The Product ID columns have different data types causing the Join to fail completely.

C The Join type should be changed to Left Join to include all Sales rows.

D The Union was used instead of Join, causing missing rows.

💡 Hint

Consider how Inner Join works with matching keys.

An Inner Join returns only rows with matching keys in both tables. If some Product IDs in Products don't exist in Sales, those rows are excluded, causing missing products.

🎯 Scenario

expert

Choosing the Right Combination Method for Data Integration

Your company has two separate Excel files: one with customer contact info and another with customer purchase history. You want to create a Tableau dashboard showing all customers with their purchase totals. Which method should you use to combine these files?

A Use a Union to stack the two tables vertically since they have different columns.

B Append the purchase history file to the contact info file manually before importing.

C Import both files separately and blend the data in Tableau without joining.

D Use a Join on Customer ID to combine contact info and purchase history horizontally.

💡 Hint

Think about how to combine related data with matching keys.

Joining on Customer ID combines contact info and purchase history horizontally, allowing analysis of customers with their purchase totals in one table.

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