Blending data sources in Tableau - Real Business Scenario

Scenario Mode

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

📋 Request: Your manager wants a report that shows total sales by product category along with customer satisfaction scores from a separate survey data source.

📊 Data: You have two data sources: 1) Sales data with columns: OrderID, ProductCategory, SalesAmount, OrderDate. 2) Customer survey data with columns: CustomerID, ProductCategory, SatisfactionScore.

🎯 Deliverable: Create a blended Tableau dashboard that combines sales totals by product category with average customer satisfaction scores for the same categories.

Sample Data

OrderID	ProductCategory	SalesAmount	OrderDate
1001	Electronics	250	2024-01-15
1002	Furniture	450	2024-01-16
1003	Electronics	300	2024-01-17
1004	Clothing	150	2024-01-18
1005	Furniture	700	2024-01-19
1006	Clothing	200	2024-01-20

CustomerID	ProductCategory	SatisfactionScore
C001	Electronics	4.5
C002	Furniture	3.8
C003	Clothing	4.2
C004	Electronics	4.0
C005	Furniture	4.1
C006	Clothing	3.9

1

Step 1: Connect to the Sales data source in Tableau.

Use 'OrderID', 'ProductCategory', 'SalesAmount', and 'OrderDate' columns.

Expected Result

Sales data loaded with 6 rows.

2

Step 2: Connect to the Customer Survey data source in Tableau.

Use 'CustomerID', 'ProductCategory', and 'SatisfactionScore' columns.

Expected Result

Survey data loaded with 6 rows.

3

Step 3: Create a new worksheet for sales totals by product category.

Rows: 'ProductCategory'; Columns: SUM('SalesAmount').

Expected Result

Table showing total sales: Electronics=550, Furniture=1150, Clothing=350.

4

Step 4: Create a new worksheet for average satisfaction score by product category.

Rows: 'ProductCategory'; Columns: AVG('SatisfactionScore').

Expected Result

Table showing average scores: Electronics=4.25, Furniture=3.95, Clothing=4.05.

5

Step 5: Blend the two data sources on 'ProductCategory' in Tableau.

Use 'ProductCategory' as the linking field between Sales and Survey data sources.

Expected Result

Blended data source created linking sales and satisfaction by product category.

6

Step 6: Create a combined view showing total sales and average satisfaction side by side.

Rows: 'ProductCategory'; Columns: SUM('SalesAmount'), AVG('SatisfactionScore') from blended data.

Expected Result

Dashboard view with columns: ProductCategory, Total Sales, Avg Satisfaction Score.

7

Step 7: Build a dashboard with the combined view and add clear titles and labels.

Add worksheet to dashboard; title: 'Sales and Customer Satisfaction by Product Category'.

Expected Result

Dashboard ready for presentation with clear, accessible visualization.

Final Result

--------------------------------------------------
| Sales and Customer Satisfaction by Product Category |
--------------------------------------------------
| ProductCategory | Total Sales | Avg Satisfaction |
|-----------------|-------------|------------------|
| Electronics     | $550        | 4.25             |
| Furniture       | $1150       | 3.95             |
| Clothing        | $350        | 4.05             |
--------------------------------------------------

✓Furniture has the highest total sales but the lowest average satisfaction score.

✓Electronics and Clothing have similar satisfaction scores above 4.0.

✓Sales and satisfaction scores vary independently by product category.

Bonus Challenge

Add a time filter to the dashboard to analyze sales and satisfaction by month.

Show Hint

Use the 'OrderDate' field from the Sales data source to create a date filter and apply it to the blended view.

Practice

1. What is the main purpose of blending data sources in Tableau?

easy

A. To create a single table by merging all data sources permanently

B. To combine data from different sources using common fields without merging tables

C. To replace the primary data source with a secondary one

D. To export data from Tableau to external databases

Solution

1. Step 1: Understand blending concept

   Blending connects data from different sources using common fields without merging them permanently.

2. Step 2: Compare options

   To combine data from different sources using common fields without merging tables correctly describes blending. Options A, C, and D describe other unrelated actions.

3. Final Answer:

   To combine data from different sources using common fields without merging tables -> Option B

4. Quick Check:

   Blending = combine without merging [OK]

Hint: Blending links data without merging tables [OK]

Common Mistakes:

• Confusing blending with joining or merging tables
• Thinking blending replaces the primary source
• Assuming blending exports data

2. Which of the following is the correct way to identify the linking field in Tableau data blending?

easy

A. The field with a red cross in the primary data source

B. The field with a blue checkmark in the secondary data source

C. The field with a green plus sign in the primary data source

D. The field with an orange chain link icon in the secondary data source

Solution

1. Step 1: Recognize linking field icon

   In Tableau, linking fields in the secondary data source show an orange chain link icon.

2. Step 2: Match options to icons

   The field with an orange chain link icon in the secondary data source correctly identifies the orange chain link icon as the linking field. Other options describe incorrect icons or colors.

3. Final Answer:

   The field with an orange chain link icon in the secondary data source -> Option D

4. Quick Check:

   Linking field = orange chain link icon [OK]

Hint: Look for orange chain link icon for linking fields [OK]

Common Mistakes:

• Confusing linking field icon with checkmarks or plus signs
• Looking for icons in the primary instead of secondary source
• Ignoring icon colors

3. Given two data sources: Primary with fields OrderID, Sales and Secondary with fields OrderID, CustomerName. If you blend on OrderID and create a view showing Sales and CustomerName, what will happen if an OrderID exists only in the secondary source?

medium

A. The view will exclude that OrderID because it is missing in the primary source

B. The view will show Sales as null and CustomerName for that OrderID

C. The view will show Sales and CustomerName as null

D. The view will cause an error and not display

Solution

1. Step 1: Understand primary source control

   In blending, the primary source controls the rows shown. If an OrderID is missing in primary, it won't appear.

2. Step 2: Analyze missing OrderID in primary

   Since the OrderID exists only in secondary, it will be excluded from the view.

3. Final Answer:

   The view will exclude that OrderID because it is missing in the primary source -> Option A

4. Quick Check:

   Primary source controls rows = missing keys excluded [OK]

Hint: Primary source controls rows shown in blending [OK]

Common Mistakes:

• Expecting secondary-only keys to appear in the view
• Thinking null values appear for missing primary keys
• Assuming blending causes errors on missing keys

4. You blended two data sources on CustomerID. However, the secondary data source fields show Null values in your view. What is the most likely cause?

medium

A. You forgot to refresh the data sources

B. The primary data source is missing the CustomerID field

C. The linking field CustomerID has mismatched data types between sources

D. The secondary data source is set as primary by mistake

Solution

1. Step 1: Check linking field compatibility

   Blending requires linking fields to have matching data types to join correctly.

2. Step 2: Identify cause of nulls

   If data types differ, Tableau cannot match keys, causing nulls in secondary fields.

3. Final Answer:

   The linking field CustomerID has mismatched data types between sources -> Option C

4. Quick Check:

   Matching data types needed for linking fields [OK]

Hint: Check data types of linking fields if nulls appear [OK]

Common Mistakes:

• Assuming missing fields cause nulls instead of mismatched types
• Confusing primary and secondary source roles
• Ignoring need to refresh data

5. You have two data sources: SalesData (Primary) with OrderID, SalesAmount and CustomerData (Secondary) with CustomerID, OrderID, Region. You want to create a view showing total sales by region. How should you blend and aggregate the data correctly?

hard

A. Blend on OrderID, use Region from secondary, and create a calculated field summing SalesAmount grouped by Region

B. Blend on CustomerID, use Region from secondary, and sum SalesAmount without grouping

C. Join the two sources on OrderID instead of blending, then sum SalesAmount by Region

D. Blend on Region, then sum SalesAmount grouped by OrderID

Solution

1. Step 1: Identify correct linking field

   OrderID exists in both sources and links sales to customer region.

2. Step 2: Blend on OrderID and aggregate

   Blend on OrderID, use Region from secondary, then sum SalesAmount grouped by Region for total sales by region.

3. Final Answer:

   Blend on OrderID, use Region from secondary, and create a calculated field summing SalesAmount grouped by Region -> Option A

4. Quick Check:

   Blend on OrderID + sum Sales by Region [OK]

Hint: Blend on common key, aggregate sales by region [OK]

Common Mistakes:

• Blending on wrong field like CustomerID or Region
• Not grouping sales by region
• Confusing blending with joining