Size encoding in Tableau - Real Business Scenario

Scenario Mode

👤 Your Role: You are a sales analyst at a retail company.

📋 Request: Your manager wants a visual report that shows sales performance by product category and region. They want to quickly see which categories and regions have higher sales volumes using size differences in the visualization.

📊 Data: You have monthly sales data including Product Category, Region, and Sales Amount.

🎯 Deliverable: Create a Tableau dashboard with a scatter plot where each point represents a product category in a region. Use size encoding to show total sales amount, so bigger points mean higher sales.

Sample Data

Month	Product Category	Region	Sales Amount
Jan	Electronics	North	12000
Jan	Furniture	North	8000
Jan	Clothing	North	6000
Jan	Electronics	South	15000
Jan	Furniture	South	7000
Jan	Clothing	South	9000
Feb	Electronics	North	13000
Feb	Furniture	North	8500
Feb	Clothing	North	6500
Feb	Electronics	South	16000
Feb	Furniture	South	7500
Feb	Clothing	South	9500

1

Step 1: Connect your sales data to Tableau and load the data source.

No formula needed; just connect the data source.

Expected Result

Sales data is available in Tableau for analysis.

2

Step 2: Create a new worksheet for the scatter plot.

No formula; just open a new worksheet.

Expected Result

Blank worksheet ready for visualization.

3

Step 3: Drag 'Product Category' to Columns shelf.

Columns: Product Category

Expected Result

Columns show product categories.

4

Step 4: Drag 'Region' to Rows shelf.

Rows: Region

Expected Result

Rows show regions.

5

Step 5: Create a calculated field to sum sales amount by category and region.

Calculated Field Name: Total Sales Formula: SUM([Sales Amount])

Expected Result

Total Sales field sums sales for each category and region.

6

Step 6: Drag 'Total Sales' to Size on the Marks card.

Marks card > Size: Total Sales

Expected Result

Point sizes vary by total sales amount.

7

Step 7: Change the mark type to Circle for better size encoding.

Marks card > Mark Type: Circle

Expected Result

Points appear as circles sized by sales.

8

Step 8: Add 'Total Sales' to Tooltip to show exact sales on hover.

Marks card > Tooltip: Add Total Sales

Expected Result

Tooltip shows total sales when hovering over points.

9

Step 9: Adjust size slider on Marks card for clear size differences.

Marks card > Size slider: Adjust for clarity

Expected Result

Size differences are visually clear and easy to compare.

10

Step 10: Create a dashboard and add this worksheet with a title 'Sales by Category and Region with Size Encoding'.

Dashboard > Add worksheet > Add title

Expected Result

Dashboard shows scatter plot with size encoding and title.

Final Result

Dashboard: Sales by Category and Region with Size Encoding

Region  | Electronics  Furniture  Clothing
------------------------------------------
North   |  ●●●●●●●●●  ●●●●●●    ●●●●
South   |  ●●●●●●●●●●●●  ●●●●●    ●●●●●

Legend: Larger circles mean higher total sales.

✓Electronics has the highest sales in both North and South regions, shown by the largest circles.

✓Furniture sales are smaller compared to Electronics but vary slightly by region.

✓Clothing sales are moderate and consistent across regions.

Bonus Challenge

Add color encoding to the scatter plot to show sales growth compared to the previous month.

Show Hint

Create a calculated field for sales growth percentage and drag it to Color on the Marks card.

Practice

1. What is the main purpose of size encoding in Tableau visualizations?

easy

A. To sort data in ascending or descending order

B. To change the color of marks based on categories

C. To filter data points from the view

D. To change the size of marks based on data values

Solution

1. Step 1: Understand size encoding concept

   Size encoding adjusts the size of visual marks to represent numeric data values visually.

2. Step 2: Compare options with concept

   Only To change the size of marks based on data values describes changing mark size based on data values, which matches size encoding.

3. Final Answer:

   To change the size of marks based on data values -> Option D

4. Quick Check:

   Size encoding = mark size by data [OK]

Hint: Size encoding changes mark size to show data amounts [OK]

Common Mistakes:

• Confusing size encoding with color encoding
• Thinking size encoding filters data
• Assuming size encoding sorts data

2. Which of the following is the correct way to apply size encoding in Tableau?

easy

A. Drag a measure field to the Color shelf

B. Drag a dimension field to the Size shelf

C. Drag a measure field to the Size shelf

D. Drag a dimension field to the Filters shelf

Solution

1. Step 1: Identify what type of field size encoding uses

   Size encoding requires numeric data, so it uses measure fields.

2. Step 2: Match correct shelf for size encoding

   Size shelf controls mark size, so dragging a measure field there is correct.

3. Final Answer:

   Drag a measure field to the Size shelf -> Option C

4. Quick Check:

   Size shelf + measure field = correct size encoding [OK]

Hint: Size encoding needs numeric (measure) fields on Size shelf [OK]

Common Mistakes:

• Using dimension fields instead of measures
• Dragging fields to Color shelf instead of Size
• Confusing Filters shelf with Size shelf

3. Given a bar chart with sales amounts encoded by size, what happens if you increase the size range in Tableau's Size legend?

medium

A. Bars with higher sales become noticeably larger compared to smaller sales bars

B. All bars become uniformly larger regardless of sales

C. Bars change color instead of size

D. The chart filters out smaller sales bars

Solution

1. Step 1: Understand effect of increasing size range

   Increasing size range makes size differences more pronounced between small and large values.

2. Step 2: Analyze impact on bars

   Bars with higher sales grow larger relative to smaller sales bars, enhancing visual comparison.

3. Final Answer:

   Bars with higher sales become noticeably larger compared to smaller sales bars -> Option A

4. Quick Check:

   Increase size range = bigger size difference [OK]

Hint: Larger size range exaggerates size differences [OK]

Common Mistakes:

• Thinking all bars grow equally
• Confusing size changes with color changes
• Assuming filtering happens automatically

4. You applied size encoding to a measure but notice all marks are the same size. What is the most likely cause?

medium

A. The measure has the same value for all data points

B. You dragged a dimension field to the Size shelf

C. The color legend is overriding size encoding

D. The data source is disconnected

Solution

1. Step 1: Check measure values for size encoding

   If all measure values are identical, size encoding cannot differentiate mark sizes.

2. Step 2: Evaluate other options

   Dragging dimension to Size shelf would cause error, color legend does not override size, and disconnected data prevents any marks.

3. Final Answer:

   The measure has the same value for all data points -> Option A

4. Quick Check:

   Same measure values = same mark size [OK]

Hint: Check if measure values vary to see size differences [OK]

Common Mistakes:

• Assuming dimension fields work for size encoding
• Thinking color affects size encoding directly
• Ignoring data connection status

5. You want to create a scatter plot where the size of each point shows the total sales per region, but some points appear too small to see. What is the best way to improve size encoding clarity?

hard

A. Remove size encoding and use color encoding instead

B. Increase the maximum size in the Size legend and use a logarithmic scale for sales

C. Filter out regions with small sales values

D. Use a dimension field on the Size shelf instead of sales

Solution

1. Step 1: Address small point visibility

   Increasing maximum size makes larger points bigger and more visible.

2. Step 2: Use logarithmic scale for better size distribution

   Log scale reduces skew from very large sales, improving size differences for smaller points.

3. Final Answer:

   Increase the maximum size in the Size legend and use a logarithmic scale for sales -> Option B

4. Quick Check:

   Max size + log scale = clearer size differences [OK]

Hint: Use max size and log scale to fix tiny marks [OK]

Common Mistakes:

• Removing size encoding loses visual comparison
• Filtering data hides information unnecessarily
• Using dimension fields for size causes errors