100+ Free Tableau Data Analyst Practice Questions

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What is the PERCENTILE() function used for in Tableau?

To calculate the percentage change between two values

To convert values to a 0-100 scale

To determine the probability of a value occurring

To return the value at a specific percentile rank in the data distribution

to track

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Key Facts: Tableau Data Analyst Exam

Exam Questions

Salesforce/Tableau exam guide (60+5 unscored)

120 min

Exam Duration

Salesforce/Tableau exam guide

65%

Passing Score

Salesforce/Tableau exam guide

$200

Exam Fee

Salesforce/Tableau 2025 pricing

24 mo

Credential Validity

Salesforce/Tableau policy

The Tableau Data Analyst exam has 60 scored questions plus 5 unscored items in 120 minutes at $200 USD. Passing score is 65%. Domains: Connect/Transform Data (24%), Explore/Analyze (41%), Create Content (26%), Publish/Manage (9%). Credential valid 24 months.

Sample Tableau Data Analyst Practice Questions

Try these sample questions to test your Tableau Data Analyst exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1In Tableau, what is the primary difference between a relationship and a join when connecting multiple tables?

A.Relationships can only connect two tables; joins can connect unlimited tables

B.Relationships preserve the native level of detail of each table and resolve queries at runtime; joins physically combine rows before analysis

C.Joins are faster than relationships in all scenarios

D.Relationships require matching data types; joins do not

Explanation: Relationships define logical connections between tables that Tableau resolves at query time, preserving each table's native granularity. Joins physically merge rows before analysis, potentially creating data duplication. Relationships are the recommended approach since Tableau 2020.2.

2When should you use an extract instead of a live connection in Tableau?

A.When you need real-time data that updates every second

B.When you need faster performance, offline access, or want to reduce load on the source database

C.When you want to avoid storing any data locally

D.When the data source is a simple CSV file

Explanation: Extracts are ideal when you need faster query performance (the .hyper engine is optimized for analytics), offline access when disconnected from the network, or reduced load on production databases. Extracts can also apply incremental refreshes and row/column filters to minimize data size.

3What is the purpose of Tableau Prep Builder in the data analyst workflow?

A.To create visualizations and dashboards

B.To clean, combine, shape, and prepare data for analysis before loading it into Tableau Desktop

C.To schedule automated report delivery

D.To manage user permissions on Tableau Server

Explanation: Tableau Prep Builder is a dedicated data preparation tool that provides a visual, drag-and-drop interface for cleaning, transforming, combining (joining, unioning), pivoting, and reshaping data. Its output feeds directly into Tableau Desktop for analysis.

4Which LOD expression in Tableau computes at a specified dimension level regardless of the dimensions in the view?

A.INCLUDE

B.EXCLUDE

C.FIXED

D.TOTAL

Explanation: FIXED LOD expressions compute an aggregation at the exact dimension level specified, independent of what dimensions appear in the view. For example, {FIXED [Customer] : SUM([Sales])} always computes total sales per customer regardless of the view's granularity.

5In a Tableau table calculation, what is the difference between 'Compute Using' (addressing) and 'Partitioning'?

A.They are the same concept with different names

B.Addressing defines the direction the calculation moves; partitioning defines the groups within which the calculation resets

C.Addressing applies to measures; partitioning applies to dimensions

D.Partitioning determines the chart type; addressing determines the axis

Explanation: Addressing (Compute Using) defines the direction a table calculation traverses — across, down, or by a specific dimension. Partitioning defines the independent groups within which the calculation restarts. Together they determine exactly how a table calculation processes data.

6What is the correct syntax for a FIXED LOD expression that calculates the average order value per customer?

A.FIXED [Customer ID] : AVG([Order Value])

B.{ FIXED [Customer ID] : AVG([Order Value]) }

C.LOD(FIXED, [Customer ID], AVG([Order Value]))

D.CALCULATE(AVG([Order Value]), FIXED [Customer ID])

Explanation: LOD expressions in Tableau must be enclosed in curly braces: { FIXED [Customer ID] : AVG([Order Value]) }. The syntax is { LOD_TYPE [dimension(s)] : AGGREGATE([measure]) }. Without curly braces, the expression is invalid.

7How do data source filters interact with FIXED LOD expressions in Tableau?

A.Data source filters are ignored by FIXED LOD expressions

B.Data source filters are applied before FIXED LOD expressions, limiting the data available to them

C.FIXED LOD expressions override data source filters

D.Data source filters and FIXED LOD expressions cannot be used together

Explanation: In Tableau's order of operations, data source filters (and extract filters) are applied before FIXED LOD expressions. This means FIXED LOD calculations only see data that passes the data source filter. However, dimension filters applied through the Filters shelf do NOT affect FIXED LOD expressions.

8When creating a dashboard in Tableau, what is the advantage of using container-based layouts?

A.Containers automatically create animations between views

B.Containers allow you to group objects that resize and reposition together, maintaining proportional layout

C.Containers reduce the file size of the workbook

D.Containers are required for publishing to Tableau Server

Explanation: Horizontal and vertical containers group dashboard objects so they resize proportionally together. When the dashboard or browser window is resized, contained objects maintain their relative positions and proportions, creating responsive layouts.

9What is the purpose of a parameter action in a Tableau dashboard?

A.To create a new parameter when a button is clicked

B.To update the value of an existing parameter based on user interaction with marks in a visualization

C.To delete parameters that are no longer needed

D.To export parameter values to a file

Explanation: Parameter actions dynamically update a parameter's value when a user interacts with marks (click, hover, or select) in a visualization. This enables scenarios like clicking a bar to set a reference value, or selecting a category to drive calculations across the dashboard.

10What is the difference between Tableau's RUNNING_SUM() and WINDOW_SUM() table calculations?

A.They produce identical results in all cases

B.RUNNING_SUM() computes a cumulative total from the first row to the current row; WINDOW_SUM() computes a sum over a specified range of rows

C.RUNNING_SUM() works on dimensions; WINDOW_SUM() works on measures

D.WINDOW_SUM() is faster because it processes fewer rows

Explanation: RUNNING_SUM() calculates a cumulative total that grows as it processes each row from first to current. WINDOW_SUM() calculates the sum over a defined window (start offset to end offset), which can be a fixed range, a trailing window, or the entire partition.

About the Tableau Data Analyst Exam

The Salesforce Certified Tableau Data Analyst exam validates intermediate analytics skills including LOD expressions, table calculations, Tableau Prep, data modeling, dashboard design, and Server/Cloud publishing.

Questions

60 scored questions

Time Limit

2 hours

Passing Score

65%

Exam Fee

$200 (Salesforce/Tableau)

Tableau Data Analyst Exam Content Outline

24%

Connect to and Transform Data

Data sources, relationships, joins, extracts, Tableau Prep, and data quality

41%

Explore and Analyze Data

LOD expressions, table calculations, parameters, statistical features, and forecasting

26%

Create Content

Advanced charts, dashboards, stories, actions, and device-specific layouts

Publish and Manage Content

Server/Cloud publishing, permissions, extract refreshes, and governance

How to Pass the Tableau Data Analyst Exam

What You Need to Know

Passing score: 65%
Exam length: 60 questions
Time limit: 2 hours
Exam fee: $200

Keys to Passing

Complete 500+ practice questions
Score 80%+ consistently before scheduling
Focus on highest-weighted sections
Use our AI tutor for tough concepts

Tableau Data Analyst Study Tips from Top Performers

1Focus heavily on Explore and Analyze Data (41%) as the largest domain

2Master all three LOD expression types: FIXED, INCLUDE, EXCLUDE

3Practice table calculations with different addressing and partitioning

4Know Tableau Prep workflows: cleaning, joining, unioning, pivoting

5Understand dashboard actions: filter, highlight, URL, parameter, and set actions

Frequently Asked Questions

How many questions are on the Tableau Data Analyst exam?

The exam has 60 scored multiple-choice/multiple-select questions plus 5 unscored items, to be completed in 120 minutes.

What score do I need to pass?

The passing score is 65%. Tableau reports percentage scores for this exam.

How much does the exam cost?

The exam costs $200 USD plus applicable taxes.

How long is the Tableau Data Analyst certification valid?

The credential is valid for 24 months. To maintain it, retake and pass the current exam.