Multiple data sources in Tableau - Dashboard Guide

Dashboard Mode - Multiple data sources

Business Question

How can we combine sales data and customer data from two different sources to analyze total sales by customer region?

Sample Data

Sales Data (Source 1)

Order ID	Customer ID	Sales Amount
1001	C001	250
1002	C002	450
1003	C003	300
1004	C001	150
1005	C004	500

Customer Data (Source 2)

Customer ID	Customer Name	Region
C001	Alice	East
C002	Bob	West
C003	Charlie	East
C004	Diana	South
C005	Eva	West

Dashboard Components

• KPI Card: Total Sales
  Formula: SUM([Sales Amount])
  Result: 1650
• Bar Chart: Sales by Region
  Data: Join Sales Data and Customer Data on Customer ID
  Calculation: Sum of Sales Amount grouped by Region
  Results:
  • East: 700 (Alice 250+150 + Charlie 300)
  • West: 450 (Bob 450)
  • South: 500 (Diana 500)
• Table: Sales Details with Customer Info
  Columns: Order ID, Customer Name, Region, Sales Amount
  Data: Joined data from both sources

Dashboard Layout

+----------------------+-----------------------+
|      Total Sales      |     Sales by Region    |
|       (KPI Card)      |       (Bar Chart)      |
+----------------------+-----------------------+
|          Sales Details Table                |
|                                              |
+----------------------------------------------+

Interactivity

A filter on Region allows users to select one or more regions. When a region is selected:

• The Sales by Region bar chart updates to show only the selected regions.
• The Total Sales KPI card recalculates the sum of sales for the selected regions.
• The Sales Details table filters to show only orders from customers in the selected regions.

This filter connects both data sources through the Region field after the join.

Self Check

Question: Add a filter for Region = East. Which components update and what are their new values?

Answer:

• Total Sales KPI card updates to 700.
• Sales by Region bar chart shows only the East region bar with value 700.
• Sales Details table shows orders 1001, 1003, and 1004 with customer names Alice and Charlie and their sales amounts.

Key Result

Dashboard combining sales and customer data from two sources to show total sales and sales by customer region.

Practice

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

easy

A. To create multiple dashboards separately

B. To combine data from different places into one view

C. To increase the size of a single data file

D. To export data to Excel automatically

Solution

1. Step 1: Understand the concept of multiple data sources

   Multiple data sources allow Tableau to bring together data from different origins.

2. Step 2: Identify the main benefit

   This lets users analyze combined data in one view without merging files physically.

3. Final Answer:

   To combine data from different places into one view -> Option B

4. Quick Check:

   Multiple data sources = Combine data [OK]

Hint: Multiple data sources combine data from different places [OK]

Common Mistakes:

• Thinking it only creates separate dashboards
• Believing it increases file size
• Confusing it with exporting data

2. Which of the following is the correct way to create a relationship between two data sources in Tableau?

easy

A. Drag a field from one source to a matching field in the other source

B. Use the Data menu to export both sources to CSV

C. Manually merge the data files outside Tableau

D. Create a calculated field with SUM() in both sources

Solution

1. Step 1: Identify how Tableau links data sources

   Tableau uses relationships by matching fields between sources to combine data logically.

2. Step 2: Recognize the correct method

   Dragging a field from one source to a matching field in another creates this relationship inside Tableau.

3. Final Answer:

   Drag a field from one source to a matching field in the other source -> Option A

4. Quick Check:

   Relationship creation = Drag matching fields [OK]

Hint: Drag matching fields to create relationships [OK]

Common Mistakes:

• Trying to export data to CSV for relationships
• Merging files outside Tableau instead of inside
• Using calculated fields incorrectly for relationships

3. Given two data sources: Sales and Targets, blended on 'Region', what will happen if a region exists in Sales but not in Targets when blending?

medium

A. The region will be excluded from the view entirely

B. Tableau will throw an error and stop loading data

C. Sales data for that region will show, but Target values will be null

D. Target values will be duplicated for that region

Solution

1. Step 1: Understand blending behavior with unmatched keys

   When blending, if a key exists in the primary source but not in the secondary, Tableau shows primary data but leaves secondary fields blank.

2. Step 2: Apply this to the region example

   Sales data for the unmatched region appears, but Targets show null because no matching region exists there.

3. Final Answer:

   Sales data for that region will show, but Target values will be null -> Option C

4. Quick Check:

   Blending unmatched keys = Primary shows, secondary null [OK]

Hint: Unmatched blend keys show primary data, secondary null [OK]

Common Mistakes:

• Assuming unmatched regions are excluded
• Expecting errors on unmatched keys
• Thinking secondary data duplicates

4. You created a blend between two data sources but notice the data is not matching correctly. What is the most likely cause?

medium

A. You used a calculated field instead of a dimension

B. You forgot to refresh the data extract

C. The dashboard has too many sheets

D. The linking fields have different data types or mismatched values

Solution

1. Step 1: Identify common blending issues

   Blending depends on matching fields; if data types or values differ, matches fail.

2. Step 2: Recognize the cause of mismatched data

   Different data types (e.g., string vs number) or inconsistent values prevent correct blending.

3. Final Answer:

   The linking fields have different data types or mismatched values -> Option D

4. Quick Check:

   Blending mismatch = Data type/value mismatch [OK]

Hint: Check data types and values of linking fields first [OK]

Common Mistakes:

• Blaming dashboard complexity
• Ignoring data refresh needs
• Confusing calculated fields with linking fields

5. You want to analyze sales data from two different databases: one with daily sales and another with monthly targets. How should you combine these in Tableau to compare performance effectively?

hard

A. Use relationships to link the data sources on the month field and blend the data

B. Join the two databases on the day field using an inner join

C. Export both datasets to Excel and merge manually before importing

D. Create separate dashboards for daily sales and monthly targets without linking

Solution

1. Step 1: Identify the best way to combine different granularity data

   Daily sales and monthly targets have different time levels, so joining on day would exclude unmatched data.

2. Step 2: Use relationships and blending on month field

   Linking on month lets Tableau combine data logically without losing unmatched days, enabling effective comparison.

3. Final Answer:

   Use relationships to link the data sources on the month field and blend the data -> Option A

4. Quick Check:

   Different granularity = Use relationships and blend [OK]

Hint: Link on common granularity (month) and blend data [OK]

Common Mistakes:

• Joining on day excludes unmatched data
• Merging outside Tableau wastes time
• Keeping dashboards separate loses combined insight