Data relationships model in Tableau - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a relationship between two tables in Tableau.

Tableau

RELATE TABLE Orders TO Customers ON Orders.CustomerID [1] Customers.CustomerID

Drag options to blanks, or click blank then click option'

A=

BIN

CLIKE

DJOIN

Attempts:

3 left

💡 Hint

Common Mistakes

Using SQL join keywords instead of equality operator.

In Tableau, relationships between tables are defined by matching keys using the equals sign (=).

2fill in blank

medium

Complete the code to specify the cardinality of a relationship in Tableau.

Tableau

CREATE RELATIONSHIP BETWEEN Orders AND Customers WITH CARDINALITY [1]

Drag options to blanks, or click blank then click option'

AMany-to-Many

BOne-to-Many

CMany-to-One

DOne-to-One

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing the direction of cardinality.

Typically, the relationship from Customers to Orders is one-to-many, meaning one customer can have many orders.

3fill in blank

hard

Fix the error in the relationship definition code.

Tableau

RELATE TABLE Sales TO Products ON Sales.ProductID [1] Products.ProductKey

Drag options to blanks, or click blank then click option'

A=

B==

C===

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using programming language equality operators instead of Tableau syntax.

Tableau uses a single equals sign (=) to define relationships between keys, not double or triple equals.

4fill in blank

hard

Fill both blanks to define a relationship with referential integrity and cardinality.

Tableau

DEFINE RELATIONSHIP BETWEEN Orders AND Customers ON Orders.CustomerID [1] Customers.CustomerID WITH CARDINALITY [2]

Drag options to blanks, or click blank then click option'

A=

BOne-to-Many

CMany-to-One

DLIKE

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong operators or confusing cardinality directions.

The relationship uses '=' to match keys and 'One-to-Many' to specify cardinality from Customers to Orders.

5fill in blank

hard

Fill all three blanks to create a relationship with matching keys, cardinality, and referential integrity.

Tableau

CREATE RELATIONSHIP BETWEEN Sales [1] Products ON Sales.ProductID [2] Products.ProductID WITH CARDINALITY [3]

Drag options to blanks, or click blank then click option'

AAND

B=

CMany-to-One

DOR

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'OR' instead of 'AND', or wrong cardinality.

The 'AND' connects tables, '=' matches keys, and 'Many-to-One' defines cardinality from Sales to Products.

Practice

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

easy

A. To delete unrelated tables automatically

B. To permanently combine tables into one

C. To create duplicate copies of data

D. To connect tables without merging them immediately

Solution

1. Step 1: Understand what data relationships do

   Data relationships link tables by matching key fields but keep tables separate until analysis.

2. Step 2: Compare with other options

   Options A, B, and C describe deleting, permanently combining, or duplicating, which are not the purpose of relationships.

3. Final Answer:

   To connect tables without merging them immediately -> Option D

4. Quick Check:

   Relationships connect tables without merging [OK]

Hint: Relationships link tables without merging data [OK]

Common Mistakes:

• Confusing relationships with joins
• Thinking relationships merge tables immediately
• Assuming relationships duplicate data

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

easy

A. Write a SQL JOIN statement manually

B. Drag a field from one table to the matching field in another table

C. Copy data from one table and paste into another

D. Use the Data Interpreter to merge tables

Solution

1. Step 1: Identify how Tableau creates relationships

   Tableau allows creating relationships by dragging a key field from one table to the matching field in another.

2. Step 2: Eliminate incorrect methods

   Options A, C, and D describe manual SQL, copying data, or using Data Interpreter, which are not how relationships are created.

3. Final Answer:

   Drag a field from one table to the matching field in another table -> Option B

4. Quick Check:

   Drag matching fields to create relationships [OK]

Hint: Drag matching keys between tables to create relationships [OK]

Common Mistakes:

• Trying to write SQL JOINs instead of using drag-and-drop
• Copy-pasting data instead of linking tables
• Confusing Data Interpreter with relationships

3. Given two tables: Orders with fields OrderID, CustomerID and Customers with fields CustomerID, CustomerName, what will happen if you create a relationship on CustomerID and then create a view showing CustomerName and count of OrderID?

medium

A. The view shows each customer with the number of their orders

B. The view shows all orders without customer names

C. The view shows customer names but no order counts

D. The view causes an error due to missing join

Solution

1. Step 1: Understand relationship on CustomerID

   Relationship links Orders and Customers on CustomerID, allowing data from both tables to combine logically.

2. Step 2: Analyze the view with CustomerName and count(OrderID)

   Tableau aggregates orders per customer, showing customer names with their order counts.

3. Final Answer:

   The view shows each customer with the number of their orders -> Option A

4. Quick Check:

   Relationship on CustomerID aggregates orders by customer [OK]

Hint: Relationship on key fields enables combined aggregation [OK]

Common Mistakes:

• Expecting no aggregation without explicit join
• Thinking relationship causes errors
• Assuming customer names won't appear without join

4. You created a relationship between two tables on ProductID, but your view shows incorrect totals. What is the most likely cause?

medium

A. The relationship was created on non-matching fields

B. The tables are physically merged instead of related

C. You forgot to refresh the data source

D. The relationship uses fields with different data types

Solution

1. Step 1: Check the fields used in the relationship

   If the relationship is created on fields that do not match correctly, the data will not combine as expected, causing wrong totals.

2. Step 2: Evaluate other options

   Data type mismatch usually prevents relationship creation; physical merge creates a single table instead of relating; refreshing rarely fixes relationship logic errors.

3. Final Answer:

   The relationship was created on non-matching fields -> Option A

4. Quick Check:

   Incorrect totals often mean wrong relationship fields [OK]

Hint: Verify relationship fields match exactly to fix totals [OK]

Common Mistakes:

• Ignoring field mismatches in relationships
• Assuming refresh fixes relationship logic
• Confusing relationships with joins or merges

5. You have three tables: Sales (with SaleID, ProductID, DateID), Products (with ProductID, ProductName), and Dates (with DateID, Date). How should you set up relationships to analyze total sales by product name and date?

hard

A. Create a relationship from Products to Dates directly

B. Join all three tables into one large table before analysis

C. Create relationships from Sales to Products on ProductID and from Sales to Dates on DateID

D. Create relationships from Products to Sales on ProductName and from Dates to Sales on Date

Solution

1. Step 1: Identify keys for relationships

   Sales table contains foreign keys ProductID and DateID linking to Products and Dates tables respectively.

2. Step 2: Set relationships on matching keys

   Create relationships from Sales to Products on ProductID and from Sales to Dates on DateID to enable combined analysis.

3. Step 3: Eliminate incorrect options

   Joining all tables into one is not necessary; relating Products to Dates directly lacks a direct key; using ProductName and Date for relationships are incorrect keys.

4. Final Answer:

   Create relationships from Sales to Products on ProductID and from Sales to Dates on DateID -> Option C

5. Quick Check:

   Relationships use foreign keys from fact to dimension tables [OK]

Hint: Link fact table keys to dimension tables for analysis [OK]

Common Mistakes:

• Trying to relate dimension tables directly without fact table
• Using descriptive fields instead of keys for relationships
• Joining tables unnecessarily instead of relating