Tableau is a popular data analysis and visualisation software that many businesses use to organise data. When interviewing for a role that requires expertise in Tableau, you can expect a variety of questions to assess your knowledge and skills. Reviewing some common questions and practising your answers can help you prepare better and improve your chances of clearing the interview. In this article, Pritish Kumar Halder shares 11 frequently asked Tableau interview questions with sample answers for your reference.

11 Tableau interview questions and sample answers

For an impressive performance in your interview, review the following Tableau interview questions:

1. What do you know about data types?

When the interviewer asks this question, they expect you to define different data types and discuss them. You can explain them to demonstrate your knowledge about this topic in your response. The example below explains how you can respond to a question like this.

Example answer: “There are several data types to use in Tableau as values. These are string or text, numerical, date and time, boolean, date and geographical values. Tableau can show data based on whether the field is discrete or continuous. For instance, blue colour signifies discrete and green signifies continuous. These colours signify ‘different and independent’ for discrete and ‘unseparated chain of a whole’ for continuous.”

2. How proficient are you with Tableau?

Through this question, the hiring manager wants to know your expertise with Tableau. While answering, you can discuss how knowledgeable you are with Tableau, citing previous examples of you using the program. Use the example below to guide how to answer a similar question.

Example answer: “I became a Tableau-certified data analyst about three years ago. Since then, I have consistently been undertaking business analytics at my current organisation by compiling and organising data. With the use of the programming language, SQL, I visualise and query data and transfer information between internal and external sources.”

3. What is the difference between dimensions and measures?

Here, the interviewer wants to assess your knowledge of dimensions and measures. In your response, you can highlight the difference between the two by explaining that dimensions are values with qualitative information while measures include numeric data that is quantitative. Consider this example as a reference for answering a similar question.

Example answer: “Dimensions are values that carry qualitative information such as geographical location and dates. Conversely, measures are numeric and possess quantitative data such as sales values. In my previous role, I used dimensions to efficiently organise and analyse the data of the organisation. I also used measures as aggregates.”

4. How would you differentiate between live connection and extract?

The interviewer wants to assess your knowledge of basic Tableau concepts through this question. In your response, highlight that you understand their different functions and are aware of the importance of not confusing them. Show this difference by highlighting what each one does and relating them to real situations.

Example answer: “Live connection changes at the moment of updating data source. A suitable example is hospitals requiring live information about the number of patients so that they can act according to real-time data. Conversely, data extracts are pieces of data that one can aggregate and store in the memory of the device for use at a later time. For instance, hospitals use monthly or weekly patient information through data extracts. On creating the data, access to the source database is not necessary as Tableau can make analysis and illustrations on its own.”

5. What aspect of Tableau is essential for data cleaning and visualisation?

The answer to this question helps the interviewer assess how you can use different features of the program to organise and maintain data. Here, you can discuss how you previously used these features to complete tasks. The example below can guide you in answering the question.

Example answer: “Occasionally, I use Tableau’s reader for visualisation, and I use the highlighting and filtering features for data cleaning. These Tableau features assist in dashboard creation which enables mobile compatibility.”

6. Which features of Tableau require measurement of data?

The hiring manager wants to check how you put new data in a system. This question also helps evaluate your analytical thinking and organisational skills. In your response, you can explain to the interviewer how you use the features in Tableau’s parameter to input and organise data.

Example answer: “Measurement of data is useful for differentiating between quantitative and numerical data. Recently, I measured data to collate and project the financial details of my organisation. With my knowledge and experience in Tableau, I used different measurement tags to organise the financial details like income, purchases made and profits.”

7. How do you differentiate data sources?

By asking this question, the interviewer wants to know whether you can distinguish between sources of data. In your response, you can discuss how to identify, collect and put data together. You can explain how you do these from either internal or external sources.

Example answer: “If a system has several files of data, I would identify and distinguish between the sources of data. The name of the file can help in knowing the source of information. Additionally, with the date and location information of the latest extraction, I can easily know and distinguish different data sources. I can also check the link between location and the type of connection to distinguish data sources while considering how much information is between files.”

8. Differentiate between sets and groups in Tableau

Employers know that the knowledge of sets and groups is paramount to understanding Tableau because these two factors greatly impact the system and are sometimes confused for one another. While answering this question, you can define the two through an example.

Example answer: “There are significant differences between sets and groups. You can implement Tableau groups to develop a level of category that surpasses the one-dimensional category through lower-level parts of the category. Tableau sets are subject to conditions, and you can categorise them through several measures or dimensions.

For example, say you consider two values, the number of customers and their relation to total profits. In groups, regardless of the changes in the profit, the number of customers remains unchanged. Conversely, in sets, the customers change as the profits change. When you group a subcategory, you can join the customer and profit together to make it a set.”

9. What do you understand about filters?

This is a simple but common question that hiring managers can ask. They expect you to define what filters are and give some examples. Consider using the example below while preparing your response.

Example answer: “The use of Tableau filters is inevitable in the program. Tableau filters are features that help restrict the type of data entering the view, workbook and dashboard of Tableau. There are several types of filters like data source filters, context filters, table calculation filters, extract filters, measure filters and dimension filters.”

10. Explain the differences between data joining and data blending

This question aims to test your knowledge of basic Tableau functions and features. While answering the question, you can define them and explain how they differ. If required, you can also discuss their similarities.

Example answer: “Data blending refers to the combination of data from two or more data sources where each data source has its set of measures and dimensions. Data joining is the combination of data within the same source of data but between two or more sheets or tables. These combined sheets or tables have the same set of measures and dimensions.”

11. What is the application of dimensional input?

Hiring managers can ask this question to assess your knowledge about some parameters that enhance data accessibility and usability in teamwork. While answering the question, you can explain the importance of dimensional inputs and demonstrate your analytical skills.

Example answer: “In one of my projects, I categorised some data with dimensional parameters. From my previous experience in organising information for sales and marketing purposes, I know that when I use dimensions to create segments for marketers, it helps make the campaign more efficient.”