Meaningful insights will be useless if the users and clients don’t understand it. Thus, it is crucial to present data in easy-to-use formats that a layperson can get seamlessly. Data visualization is the best solution to foster greater understanding by demystifying difficult data and showcasing it in a visually appealing way. The market size of data visualization is projected to touch the value of US $9.84 billion in 2024. (Source: Mordor Intelligence)

What is Data Visualization?

Data visualization, also known as information visualization, refers to the process of presenting, conveying, and transforming data visually. Initially, data is available in tabular reports, but visualization allows using a chart, bar, graph, and many more visual aids. It is one of the in-demand skills in data science career that is important to learn to visualize the data so that it can be used to make conclusions.

Finance, data science/research, healthcare, politics, and logistics are some industries that benefit the most from data visualization. It is used in determining correlations between two variables, network examination, frequency determination, tracking data trend changes over time, and timeline scheduling.

How to Crack an Interview for a Data Visualization Job?

Most data science jobs require professionals with expertise in data visualization to leverage their data for informed decision-making. It requires technological knowledge and a detailed understanding of converting complex data into comprehensible graphics. The following are some tips recommended by industry experts to pass the interview for your job.

  1. Develop your portfolio.

Your portfolio holds great value in an interview as it is evidence of how you have grown, your creativity level, and how efficient you are in transforming data into meaningful and understandable information.

Be sure that your portfolio features different projects to highlight your ability to work with different sorts of data and firms. The recruiter or an employer must be able to get the complete story promptly i.e. the data challenges you encountered, issues you resolved, or the effect of your visualization.

Develop a well-organized portfolio that showcases your professional and imagination skills. It must show an employer how your proficiency has enhanced over time and how you have emerged as a capable visualizer. After creating your portfolio, read and review it thoroughly to showcase all your strengths that make you a deserving candidate for them.

  1. Storytelling

To show your storytelling ability, talk about the ways you arrange your visuals to convey a practical story. Be sure to mention projects where you adopted data storytelling skills to impact decisions and make them understandable for users.

Understanding the audience and customizing the story based on their understanding extent helps in creating the most successful data story. At the same time, conveying intricate concepts is helpful irrespective of the users you are interacting with. Make sure that you clearly describe the process of data storytelling creation process, annotation usage, and effective placement of important concepts in visualizations.

  1. Popular visualization tools

Knowledge of popular data visualization tools like D3.js, Tableau, and Power BI is important, and you must be ready to share your expertise and experience with them. Assess projects in which you have leveraged different tools and technologies to create impactful visualization.

Discuss how you decide which tool to use for a certain project, and what its pros, cons, and impact on the overall power of visualization. You must be capable of expressing your expertise with several tools and your dedication to staying updated with the new trends and latest technological breakthroughs.

  1. Visually engaging and simplicity

Visualization in a data science career is an imperative skill that helps in making data insights comprehensible to every user. Therefore, you must pay attention to discussing your ability to present appealing and informative images. Discuss your understanding of color theory, design concepts, and font choices.

Let an interviewer know how capable you are of keeping a perfect balance of clarity and originality to make visualizations engaging and logical. This ability is in high demand among recruiters and employers. Knowing the art of making visualizations easier to remember and more appealing to users can make you stand out among other candidates. Highlight your achievements and obstacles you face when balancing simplicity and clear communication.

  1. Problem-solving

This is one of the must-have skills in data science job profiles as it helps in effectively dealing with problems. You must be ready with an example of how your visualization skills and techniques helped in solving challenging issues and making better decisions. Discuss how you decide which solution will work perfectly in a specific problematic situation and what results came from visualizations.


Employers or recruiters are interested in discovering how technically proficient you are and how you would use those skills perfectly in your visualizations. To easily crack your interview, you must be ready with knowledge of fundamental concepts, data analysis skills, visualization tools and techniques, industry trends, and design challenges. Showcase your communication skills and approach your interview with full confidence.