Tableau Interview Questions : How to Pass a Tableau Developer Interview

There is no way to really know what questions you will be asked at an interview for a Tableau developer job. However, you do need to master some the concepts so that you inherently posses the flexibly to answer whatever the interviewer happens to throw at you. In this comprehensive post, you are going to understand key concepts and questions you must be able to answer. Here is the agenda that we will cover:

  • # 1 Tableau Interview Question
  • Preparing Before the Interview.
  • Fundamental Concepts that you should master!
  • Tableau Interview Questions and Answers

The #1 Tableau Interview Question

Without fail having an answer to this question will give you a distinct advantage over other candidates and also make your interviews go a lot smoother.

Do You Have a Tableau Dashboard Portfolio?

Some form of this question will pop up 1000000%. So let me explain why you must have a Tableau dashboard and why it helps to avoid you getting caught in an endless cycle of questions and answers and actually allows you to demonstrate your skills and creativity.

  1. Demonstrates your skills: It allows you to showcase your ability to create effective data visualizations and dashboards, which is a key skill in many data-related roles.
  2. Shows your creativity and problem-solving abilities: It shows that you are able to take complex data and turn it into meaningful insights and that you can design effective and visually appealing dashboards that convey information in a clear and concise way.
  3. Differentiates you from other candidates: Having a portfolio can help you stand out from other candidates who may not have as much experience or a similar portfolio.
  4. Provides a starting point for discussion: During the interview, you can use your Tableau dashboard portfolio as a starting point for discussion. You can walk through your thought process, design choices, and the data behind each dashboard, which can help to showcase your expertise and provide more insight into your approach to data analysis.

I would even go as far as to host your dashboard Portfolio on Tableau Public and simply send this over to them prior to the interview. If you want to see my Tableau Portfolio which has gotten me a few jobs take a look.

My Simple Tableau Portfolio

How to Prepare for a Tableau Interview

  • Portfolio: Get your Tableau Dashboard Portfolio ready and optimized with examples for the interview
  • Build a New Dashboard: This will help you refresh your fundamental knowledge and talk about current things you are working on
  • Review a Question repository: see below
  • Prepare Your Own Questions: Creating a repour with the interviewer shows that you are able to communicate, are prepared, and can be a team player. Don’t skip this step!

Tableau Calculations You Should Know

Learning these intermediate to advanced Tableau calculations can significantly improve your data analysis skills and cover everything you would potentially need to create standard reports. Top 40 Tableau Calculations.

CalculationDescriptionExample
IF StatementsCreate conditional logic based on data valuesIF [Sales] > 1000 THEN "High" ELSE "Low" END creates a new calculated field that categorizes sales data as either “High” or “Low” based on a threshold of 1000
Date CalculationsManipulate dates and times in TableauDATEDIFF('day', [Order Date], [Ship Date]) calculates the difference in days between the order date and the ship date
Table CalculationsPerform calculations across rows and columns in a Tableau viewWINDOW_SUM(SUM([Sales])) / TOTAL(SUM([Sales])) calculates the percent of the total for each category in a stacked bar chart
LOD ExpressionsPerform calculations at a specific level of detail{ FIXED [Customer Name] : SUM([Sales]) } calculates the sum of sales by customer, regardless of the other dimensions used in the view
String CalculationsManipulate text in TableauLEFT([Customer Name], 1) creates a new field with the first letter of the customer’s name
ParametersCreate interactive controls in TableauDATEADD('day', -[Date Range], TODAY()) uses a parameter to adjust the date range in a view
Logical FunctionsPerform Boolean logic in TableauIF [Sales] > 1000 AND [Profit] > 500 THEN "High Margin" ELSE "Low Margin" END creates a new field that categorizes sales data based on both sales and profit thresholds

Key Concepts to Know Prior to the Interview

  1. Data types: Understand the different types of data that can be used in Tableau, including dimensions, measures, and discrete and continuous data types.
  2. Connecting to data sources: Know how to connect to various data sources, such as Excel, CSV files, SQL databases, and cloud-based data sources.
  3. Creating visualizations: Be familiar with the different types of visualizations in Tableau, including charts, graphs, maps, and tables, and how to create and customize them.
  4. Calculations: Understand how to create calculations and use functions in Tableau, including calculated fields, table calculations, and LOD expressions.
  5. Joins: Know how to blend data from multiple data sources in Tableau and how to resolve common issues that may arise during the blending process. Tableau Joins and Blend Tutorial
  6. Performance optimization: Understand how to optimize the performance of Tableau dashboards and visualizations, including best practices for reducing load times and improving overall performance.
  7. Dashboard design: Know how to design effective and visually appealing dashboards in Tableau, including best practices for layout, color, and interactivity.
  8. Tableau Server and Sharing Reports: Understand how to use Tableau Server to publish and share dashboards and visualizations with others, including how to manage permissions and access.
  9. Advanced topics: Be familiar with more advanced topics in Tableau, such as data densification, context filters, data extracts, and data modeling.
  10. Data analysis: Understand basic data analysis concepts and how they can be applied in Tableau to gain insights from data.

Level of Detail Calculations are a Must Learn

Level of Detail (LOD) calculations are important in Tableau because they allow you to perform calculations at a specific level of detail, regardless of the dimensions used in the view. This gives you more granular control over the level of detail of your calculations and enables you to analyze and visualize data in more nuanced ways.

Make sure that you have a full understanding of how to use the LOD functions. This is such a common ask in a technical portion of the interview process. The table below will summarize and give you an example of each. If you want to check out Quick Guide to LOD Functions in Tableau.

FunctionDescriptionExample
INCLUDECalculates the expression at a specified level of detail, including the dimension(s) in the expression{INCLUDE [Category]: AVG(Sales)} calculates the average sales by category, including the category dimension in the expression
EXCLUDECalculates the expression at a specified level of detail, excluding the dimension(s) in the expression{EXCLUDE [Sub-Category]: SUM(Profit)} calculates the sum of profit, excluding the sub-category dimension in the expression
FIXEDCalculates the expression at a specified level of detail, ignoring all other dimensions in the view{FIXED [Region], [Year]: SUM(Sales)} calculates the sum of sales by region and year, ignoring all other dimensions in the view
ATTRReturns the value of an attribute at a specified level of detail{ATTR([State])} returns the state attribute value at the specified level of detail

Follow the Detail Tutorials on LOD Functions:

Fixed LOD Function Tutorial

Include LOD Function Tutorial

Exclude LOD Function Tutorial

Tableau Interview Questions: Don’t Memorize! Understand How to Respond.

It’s important to avoid simply memorizing simple answers to Tableau interview questions. Try focusing on demonstrating a deeper understanding of the tool and its functionality. While it can be helpful to review common interview questions and prepare responses, the most effective way to succeed in a Tableau interview is to have practical experience working with the tool and to be able to think critically about data analysis and visualization. Employers are looking for candidates who can apply their knowledge and skills to real-world data challenges, so it’s important to focus on showing a deeper understanding of Tableau.

List of Tableau Interview Questions to Test Your Fundamental Knowledge

  1. What is the difference between a left join, right join, inner join, and outer join in Tableau?
  2. How would calculate the percent of total sales in each category?
  3. How do you use Table Calculations in Tableau?
  4. What is the difference between a dual-axis chart and a combined chart in Tableau?
  5. What is the purpose of the “Data Interpreter” in Tableau and when should you use it?
  6. How do you use level of detail (LOD) expressions in Tableau and why would you need it?
  7. What are the differences in using a Tableau Extract vs Live Connection?
  8. How do you use Tableau Prep to prepare data for analysis in Tableau?
  9. How would you find the Top 10 and Bottom 10 Values in your data?
  10. When do you use Sets vs Groups in Tableau?
  11. What is the difference between a table calculation and a regular calculation in Tableau?
  12. How do you create a dynamic parameter in Tableau, where the parameter values change based on the data selected?
  13. What is a context filter in Tableau and when should you use it?
  14. What is your workflow for building a Tableau dashboard?
  15. How do you optimize the performance of large and complex Tableau dashboards, and what are some best practices for designing effective dashboards?
  16. How would you best visualize the relationship between two variables?
  17. How would visualize two sets of values that are on different scales?

Experience-Based Tableau Interview Questions

These are going to really allow you to expand on all the things you were able to achieve previously being a Tableau Developer.

  1. Do you have any experience connecting Tableau to databases, live connections or APIs? Can you tell me about some challenges you’ve experienced?
  2. Do you have experience creating custom geographic maps in Tableau, and what are some best practices you’ve found for designing effective custom maps?
  3. Have you ever optimized the performance of data extracts in Tableau, and what are some strategies you’ve used to improve performance?
  4. Do you have experience using clustering algorithms in Tableau to perform data segmentation, and if so, can you share an example of how you used clustering to create more meaningful visualizations?
  5. Do you have experience integrating R or Python scripts with Tableau to perform advanced data analysis and visualization, and if so, can you describe a project where you used this technique?
  6. Have you ever created a “gantt chart” visualization in Tableau, and if so, can you walk me through the process?
  7. Do you have experience using statistical functions in Tableau to perform hypothesis testing and calculate confidence intervals, and if so, can you share an example of how you used these functions in a project?
  8. Have you ever created a “waterfall” visualization in Tableau, and if so, can you share an example of how you used this chart to communicate insights from data?
  9. Do you have experience using dynamic parameters in Tableau to create more interactive and flexible visualizations, and if so, can you describe a project where you used dynamic parameters to improve a visualization?
  10. Can you tell me about a time when you had to create a complex visualization in Tableau? How did you approach it, and what techniques did you use to overcome any challenges?
  11. Have you ever worked with large datasets in Tableau? How did you handle the performance and ensure the dashboard was user-friendly?
  12. Can you describe a scenario where you had to use Tableau to solve a business problem? What was the problem, and how did you use Tableau to address it?
  13. Have you ever used Tableau to integrate with other tools or platforms? Can you walk me through the process and the outcome of the integration?
  14. Can you explain how you have optimized Tableau dashboards for mobile devices or accessibility?
  15. Have you ever had to collaborate with other team members or stakeholders on a Tableau project? How did you manage the collaboration process, and what tools or techniques did you use?
  16. Can you tell me about a time when you had to troubleshoot a Tableau issue or error? How did you diagnose and resolve the problem?
  17. Have you ever had to migrate Tableau dashboards or reports from one environment to another? How did you ensure the migration was successful, and what challenges did you face?
  18. Can you describe a time when you had to use advanced calculations or scripting in Tableau to achieve a specific goal? What was the goal, and how did you approach the problem?
  19. Have you ever used Tableau to build predictive models or perform data analysis? Can you give an example of a project or task where you used Tableau for this purpose?

Gaelim Holland

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Nitish Jiaswal
Nitish Jiaswal
11 months ago

Thank you so much for excellent Concept