Multiple data sources in Tableau - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does 'Multiple data sources' mean in Tableau?

It means connecting and using data from more than one place or file in a single Tableau workbook to create combined views or analysis.

intermediate

What is a 'Data Blend' in Tableau?

Data Blend is a way to combine data from different sources by linking them on a common field, allowing you to analyze them together without merging the data physically.

intermediate

What is the difference between 'Data Join' and 'Data Blend' in Tableau?

Data Join combines tables from the same data source before analysis, while Data Blend combines data from different sources after aggregation, linking on common fields.

beginner

How do you add a second data source in Tableau?

You click 'Add' in the Data pane, select the new data source, and then you can use fields from both sources in your views.

beginner

Why is it important to have a common field when blending data sources?

A common field acts like a link or key to match related data from different sources, so Tableau knows how to combine the information correctly.

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

A To delete old data

B To speed up Tableau software

C To create more colors in charts

D To analyze data from different places together

Using multiple data sources lets you combine and analyze data from different places in one view.

Which method combines data from different sources after aggregation in Tableau?

A Data Join

B Data Extract

C Data Blend

D Data Filter

Data Blend links aggregated data from different sources using a common field.

What must two data sources have to blend data successfully in Tableau?

A A common field

B Same file format

C Same number of rows

D Same column names

A common field is needed to link data from different sources correctly.

How do you add a new data source in Tableau?

A Restart Tableau

B Click 'Add' in the Data pane

C Delete existing data

D Change worksheet name

You add a new data source by clicking 'Add' in the Data pane.

Which of these is NOT a way to combine data in Tableau?

A Data Filter

B Data Blend

C Union

D Data Join

Data Filter is used to limit data, not to combine data sources.

Explain how you can use multiple data sources in Tableau to create a combined report.

Think about how you link data from different places.

Describe the difference between data join and data blend in Tableau.

Consider when and how the data is combined.

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