Why connecting disparate data enables insights in Tableau - Business Case Study

Scenario Mode

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

📋 Request: Your manager wants you to show how combining sales data with customer feedback data can reveal better insights about product performance.

📊 Data: You have two data sources: one with monthly sales numbers by product and region, and another with customer satisfaction ratings by product and month.

🎯 Deliverable: Create a Tableau dashboard that connects these two data sources to show sales trends alongside customer satisfaction, highlighting products with high sales but low satisfaction.

Sample Data

Month	Product	Region	Sales
Jan	Widget A	North	120
Jan	Widget B	North	80
Feb	Widget A	South	150
Feb	Widget B	South	90
Mar	Widget A	North	130
Mar	Widget B	North	100

Month	Product	Customer Satisfaction
Jan	Widget A	4.2
Jan	Widget B	3.5
Feb	Widget A	4.0
Feb	Widget B	3.8
Mar	Widget A	4.1
Mar	Widget B	3.2

1

Step 1: Connect both data sources in Tableau by importing the Sales data and the Customer Satisfaction data.

Use Tableau's Data Source tab to add both tables and create a relationship on 'Month' and 'Product' fields.

Expected Result

Tableau links sales and satisfaction data by matching Month and Product.

2

Step 2: Create a worksheet showing total Sales by Month and Product.

Rows: Product, Columns: Month, Values: SUM(Sales)

Expected Result

A table or bar chart showing sales numbers for each product by month.

3

Step 3: Create a worksheet showing average Customer Satisfaction by Month and Product.

Rows: Product, Columns: Month, Values: AVG([Customer Satisfaction])

Expected Result

A table or line chart showing satisfaction scores for each product by month.

4

Step 4: Build a dashboard combining both worksheets side by side.

Drag both worksheets onto a dashboard layout in Tableau.

Expected Result

Dashboard displays sales and satisfaction trends together for easy comparison.

5

Step 5: Add a filter for Product to focus on specific products.

Add Product filter to dashboard and apply to both worksheets.

Expected Result

User can select a product and see its sales and satisfaction side by side.

6

Step 6: Highlight products with high sales but low satisfaction using color or annotations.

Create a calculated field: IF SUM(Sales) > 100 AND AVG([Customer Satisfaction]) < 3.5 THEN 'Attention' ELSE 'Normal' END. Use this field to color marks.

Expected Result

Products needing attention are visually distinct on the dashboard.

Final Result

Dashboard: 
+-----------------------------+-----------------------------+
| Sales by Product and Month   | Customer Satisfaction Trend  |
|                             |                             |
| Product | Jan | Feb | Mar    | Product | Jan | Feb | Mar    |
| Widget A| 120 | 150 | 130    | Widget A| 4.2 | 4.0 | 4.1    |
| Widget B|  80 |  90 | 100    | Widget B| 3.5 | 3.8 | 3.2    |
+-----------------------------+-----------------------------+
Filter: Product [All, Widget A, Widget B]
Highlights: Widget B marked in red for low satisfaction despite decent sales.

✓Widget A has consistently high sales and good customer satisfaction.

✓Widget B has moderate sales but lower customer satisfaction, especially in March.

✓Connecting sales and satisfaction data helps identify products that may need quality improvements.

Bonus Challenge

Add a trend line to the sales chart and satisfaction chart to show if performance is improving or declining over months.

Show Hint

Use Tableau's Analytics pane to drag a trend line onto each worksheet.

Practice

1. Why is connecting different data sources in Tableau important for business insights?

easy

A. It makes the dashboard load slower.

B. It combines information to give a fuller picture of the business.

C. It hides data from users.

D. It deletes duplicate records automatically.

Solution

1. Step 1: Understand the purpose of connecting data

   Connecting data sources allows combining different pieces of information that alone may not show the full story.

2. Step 2: Recognize the benefit for insights

   By linking data, Tableau can show relationships and trends that help make better decisions.

3. Final Answer:

   It combines information to give a fuller picture of the business. -> Option B

4. Quick Check:

   Connecting data = fuller picture [OK]

Hint: Connecting data = fuller insights, not slower or hidden data [OK]

Common Mistakes:

• Thinking connecting data slows dashboards
• Believing it hides data
• Assuming it deletes duplicates automatically

2. Which Tableau feature is used to link different data sources without merging their tables?

easy

A. Relationships

B. Filters

C. Calculated fields

D. Data blending

Solution

1. Step 1: Identify Tableau features for connecting data

   Tableau uses joins, relationships, and blending to connect data sources.

2. Step 2: Understand relationships

   Relationships link tables logically without merging them, preserving their structure and enabling flexible analysis.

3. Final Answer:

   Relationships -> Option A

4. Quick Check:

   Link without merging = Relationships [OK]

Hint: Relationships link data without merging tables [OK]

Common Mistakes:

• Confusing blending with relationships
• Thinking calculated fields link data
• Assuming filters connect data sources

3. Given two data sources: Sales and Customers, connected by a relationship on Customer ID, what insight can Tableau show?

medium

A. Sales data duplicated for each customer

B. Only sales data without customer info

C. Customer names without sales numbers

D. Total sales amount per customer region

Solution

1. Step 1: Understand the relationship between Sales and Customers

   The relationship on Customer ID links sales records to customer details like region.

2. Step 2: Predict the combined insight

   Tableau can aggregate sales amounts grouped by customer region using this link.

3. Final Answer:

   Total sales amount per customer region -> Option D

4. Quick Check:

   Relationship enables combined sales and customer info [OK]

Hint: Relationship joins data for combined insights like sales by region [OK]

Common Mistakes:

• Thinking only sales or only customer data shows
• Assuming data duplicates incorrectly
• Ignoring the relationship effect

4. You connected two data sources in Tableau but the dashboard shows no combined data. What is the likely problem?

medium

A. Filters are turned off.

B. The data sources have too many rows.

C. The relationship keys do not match between sources.

D. Calculated fields are missing.

Solution

1. Step 1: Check the relationship keys

   If keys used to link data do not match, Tableau cannot combine the data correctly.

2. Step 2: Rule out other causes

   Data size, filters, or calculated fields do not prevent combining if keys match.

3. Final Answer:

   The relationship keys do not match between sources. -> Option C

4. Quick Check:

   Mismatch keys = no combined data [OK]

Hint: Check keys match to connect data properly [OK]

Common Mistakes:

• Blaming data size for no combined data
• Thinking filters off cause no join
• Assuming calculated fields are required to connect

5. You have three data sources: Orders, Products, and Suppliers. How does connecting all three in Tableau help find insights?

hard

A. It allows analysis of sales by product and supplier region together.

B. It automatically cleans all data errors.

C. It hides supplier details from the report.

D. It duplicates orders for each product.

Solution

1. Step 1: Understand the role of each data source

   Orders show sales, Products describe items, Suppliers provide origin info.

2. Step 2: Connect data to combine insights

   Linking all three lets Tableau show sales by product and supplier region, revealing patterns across sources.

3. Step 3: Recognize what connecting does not do

   It does not clean errors automatically, hide data, or duplicate records incorrectly.

4. Final Answer:

   It allows analysis of sales by product and supplier region together. -> Option A

5. Quick Check:

   Connecting multiple sources = combined insights [OK]

Hint: Connect all to analyze combined sales and supplier info [OK]

Common Mistakes:

• Expecting automatic data cleaning
• Thinking data gets hidden
• Assuming data duplicates incorrectly