Data visualization questions show up regularly during data analyst interviews. In fact, if you’ve made it to the on-site round, there’s a good chance you’ll face a standalone 45-minute data visualization interview in addition to technical and behavioral rounds.
A wide variety of data visualization interview questions can come up, from basics like design philosophy and how you approach creating a visualization to Tableau technical questions. Therefore, to ace a data visualization interview, you should be prepared to:
To help you practice, we created this guide. It features an overview of what types of data visualization interview questions you can expect, as well as visualization practice questions.
Data visualization interviews tend to vary depending on the maturity of a company’s data visualization operation.
For example, a company that’s just launching a data visualization team likely hasn’t figured out its design aesthetic, what tools to use, and may not have buy-in. Therefore, the interview might focus more on your design approach, the tools that you use, and how well you collaborate.
With a more established team, you can expect more technical questions about specific tools, as well as culture fit and behavioral questions to determine if you’re right for the team.
Overall, data visualization interview topics fall into five categories::
Design philosophy questions assess your approach to data design, including color theory, types of charts, data positioning, as well as designing for specific audiences. Here are some sample design philosophy questions:
You’ll see a variation of this question in every data visualization interview. The question is asked to understand your design philosophy at a basic level and also your ability to design for a specific audience. You can talk about specific characteristics like:
One key point to hit on: Always bring your response back to the audience. Effective visualizations make data accessible for the target audience.
You should expect a color theory question. To prepare, practice talking about your favorite color theory techniques. A few to consider would be:
Tableau is one of the most widely used enterprise data visualization tools. If Tableau is mentioned in the job outreach, you should brush up on Tableau interview questions, and understand basic functions, definitions, and workflows in Tableau.
A basic question like this quickly measures how familiar you are with Tableau. Know and memorize definition-type questions like this. The data types include:
Dimensions contain qualitative values, like names, dates or locational data. Dimensions are used to segment and categorize data. Measures contain numerical quantitative values, which are measurable. Measures can be aggregated.
Data preparation and validation questions are used to assess your ability to work through challenges in data quality and processing.
Walk the interview through your data validation process. You might include preparing a data validation report, which reveals why the data failed. Next, you might discuss how you would analyze this data, and also strategies for working with missing data, like deletion, single imputation, mean/median/mode imputation, etc.
A question like this quickly assesses your experience working with data processing. Step 1 might be something like gathering stakeholder input and understanding the goals of the visualization. Then, you might include steps like:
Prepare for two types of case questions: General access questions and business case studies. General data visualization cases ask you why you might choose a particular design given a data type or scenario. More advanced business case study questions propose a business scenario, and ask you how you would design a visualization for that scenario.
A scatter plot is a type of chart that’s used to show correlation between two or more variables. Typically, it’s best used when there isn’t a time element, and can help to show the relationship between the variables, e.g. positive, negative or no correlation. For example, a scatter plot would be an effective choice to show the relationship between height and weight.
Many visualization case studies will look like this: You’ll be provided with a scenario and sample data sets, and then you must sketch a dashboard on the fly. With visualization case studies:
After you’ve gathered information, you can move to sketching out dashboard layouts to effectively display the data..
A common practice in data visualization interviews is a portfolio walk-through. You might go project by project through the portfolio, or you may be asked to highlight a few of your favorite projects.
To build a really strong visualization portfolio, you should:
During the walkthrough, be prepared to talk about each project in detail. Practice talking about:
One note: Don’t be afraid to talk about things you would do differently. This will show your ability to learn and adapt.