The Role of a Data Visualization Analyst

Data visualization is the goal of transforming complex data into a format that more people can understand. It involves visual representations of data, such as charts, graphs, and maps. These visual representations allow companies to see trends and patterns in data, which they can use to help drive sales and predict trends, among other things. A data visualization analyst focuses on these goals and aims to present complex data in a way that is understandable to all. 

Learn more about the responsibilities of a data visualization specialist, along with the educational requirements, salary, and job outlook. 

Job definition and role 

The job of a data visualization analyst can vary depending on the company. However, your main goal involves creating visualizations that convey complex data. 

What is a data visualization analyst?

A data visualization analyst works with complex data, transforming it into something more easily understood. In this job, you will often work with stakeholders to help them understand data trends, allowing them to make more informed business decisions. Data analysts work to bring order to structured data, while data visualization analysts take the data a step further, putting it into visual formats such as charts, tables, and graphs. A data visualization analyst contributes to the success of a business by not only identifying trends but understanding them as well. 

Responsibilities and tasks

Although responsibilities can differ between industries and companies, you’ll find several duties shared across most positions, including designing visualizations and communicating and collaborating with others. 

Key duties 

The following are common tasks you’ll be responsible for doing as a data visualization analyst: 

• Visualization design is the most common duty a data visualization analyst faces. It is the last step in data analysis and involves converting data collected (and analyzed) into a visual format like a graph, table, or chart (among others).

• Communicating with stakeholders: After transforming data into a visual format, you’ll want to share it with those who need the information. By creating compelling visuals you’ll be able to share data in a manner that non-technical people can understand, allowing stakeholders to make sense of complex data and identify trends and patterns that were previously “hidden.”

• Collaborating with other departments: Collaboration is a crucial part of being a data visualization analyst. You will collaborate with data analysts, engineers, stakeholders, and others. These collaborations are important to accomplish the job and get the needed results.

Depending on the structure of the company you work for, you could also be responsible for cleaning and analyzing the data you’re working with. 

Required skills and qualifications

Since one of the main tasks of a data visualization analyst is to create visualizations, it is imperative that you have some sort of design knowledge and visualization techniques, among other skills. 

Essential skills

Some of the important skills needed to perform the job of a data visualization analyst include:

• Database management: This is extremely important and will allow you to understand how to retrieve the specific data needed, making SQL an essential skill

• Design knowledge: Since your goal is to transform data sets into easy-to-understand visuals, it is imperative that you know how to use various design elements like color and arrangement to create appealing visuals. 

• Visualization techniques: It is important to know the advantages of different visualization techniques to help you decide which ones to choose in various scenarios.

• Communication skills: Solid communication skills can help in many ways, including smoothing interdepartmental collaboration. It also will help you use data storytelling to get the appropriate messages across to colleagues and stakeholders. 

Some workplace skills useful to data visualization analysts include storytelling, collaboration, and understanding your audience. 

Tools and technologies

As a data visualization analyst, you’ll be working with various visualization software, including software like Tableau. In order to succeed as a data visualization analyst, you’ll need to have some working knowledge of the software used. Popular software used includes:

• Tableau: This is frequently used for data visualization. It offers many different data visualization techniques such as dashboards, graphs, charts, tables, infographics, and geospatial, while offering more specific visualizations within each category. 

• Microsoft Power BI: This data visualization tool can take data from various sources and compile it in a single spot. It also offers various visualization options and also allows collaboration and report generation. 

• D3.js: This online JavaScript library built on web standards, can help you create custom data visualizations while providing a robust community for added support. 

Educational background

Educational requirements can vary among companies, with many employers preferring you to hold at least a bachelor’s degree in a related subject. 

Relevant degrees and certifications

If you hope to pursue a career as a data visualization analyst, consider pursuing a bachelor’s degree in one of the following fields:

• Computer science

• Graphic design

• Visual communications

• Statistics

• Data science

• Journalism

• Communication

In addition to, or instead of, a bachelor’s degree, you can also gain resume-boosting credentials like certificates and certifications, both of which can help show potential employers that you have a background and a basic understanding of data visualization. Subjects available in the field range from data visualization and advanced data visualization to more broad topics such as data science and communication through storytelling. 

Career path and advancement opportunities 

As technological advancements continue, careers in computer science are expected to grow. Explore the potential in more detail to envision your possible career path. 

Potential growth

As big data continues to become integrated into our daily lives, more and more companies are recognizing the need for data visualization analysts. Businesses are utilizing data to make informed business decisions now more than ever, and data visualization analysts are crucial to making sense of complicated data. 

The growth rate for the data visualization tools market is estimated at 11.08 percent between 2024 and 2032 [1]. Additionally, according to the US Bureau of Labor Statistics (BLS), the broad category of data scientists will grow by 36 percent between 2023 and 2033 [2].

When you consider the data, the outlook for data scientists and data visualization analysts appears to be promising. 

Industry demand and trends

Many industries employ data visualization analysts, offering various opportunities to start or continue your career in the field. Some of the top-paying industries and their corresponding base salaries include [3]:

• Financial services: $97,649

• Aerospace and defense: $93,783

• Government and public administration: $88,702

• Health care: $85,586

• Human resources and staffing: $84,574 

With the progression of big data, more and more industries will start to utilize data analytics and, more specifically, data visualization analysts. 

Sample career path for a data visualization analyst

Like so many careers, you can explore more than one path to becoming a data visualization analyst and advancing in your profession. Check out a sample of three other roles you could pursue in addition to that of data visualization analyst to envision how your journey may unfold.

Data visualization specialist

Average annual base salary: $91,422 [4]

This position will offer you opportunities to become proficient in working with visualizations. You’ll research data visualization tools and use them to help create data stories and visualizations, often testing new tools to see if they will be a good match for the company’s needs. You’ll need solid design skills and an understanding of the principles of design.

Data visualization developer

Average annual base salary: $78,398 [5]

As a data visualization developer, you’ll help create the tools that other professionals can use to build visualizations and gain a more profound understanding of the data they work with. You’ll also work to create graphs, charts, dashboards, and other business intelligence tools that you can use to create a data-driven narrative. You’ll need proficiency in front-end development and programming languages like CSS and JavaScript.

Director of data visualization 

Average annual base salary: $158,838 [6]

In this advanced-level position, you’ll play a part in your organization’s larger data strategy. You will oversee the company’s data visualization capabilities and manage it across departments.

Chief data officer (CDO)

Average annual base salary: $210,326 [7]

In this C-suite level role, you’ll take responsibility for the company’s data visualization strategies as well as the protection, governance, and use of data. You will help the organization meet its goals using data as a central strategy while overseeing data quality, data management, and business analytics.

Best practices in data visualization 

To become a successful data visualization analyst, you should master essential techniques such as formatting and using design principles. 

Effective techniques 

Consider a few things beforehand. For instance, you should have information about your audience, the goal of the visualization, and the message you’re trying to convey. 

Once you have answered those questions, you can move on to creating your visualization. Use these tips and tricks to begin. 

1. Visualization format: It is essential to choose the proper visualization for the job you want to accomplish. Many visualizations are available, such as bar charts, bullet charts, line graphs, histograms, and more. Choosing the correct visualization will help your audience connect with the information they need in a manner they can readily understand. 

2. The use of color: This can accentuate and highlight specific information, but too much of it can be overwhelming. Make sure to use simple colors in thoughtful ways that make sense. Keep in mind what people already naturally associate with specific colors and use that to your advantage. For example, people often associate red and blue with hot and cold, respectively. 

3. The use of shapes and designs: Structures and styles can intuitively provide context clues and allow people to recognize patterns easily. 

4. Text size: Similar to color, text size can accentuate and highlight specific information. The human eye naturally goes to the most prominent text on the page, so use this to your advantage. 

Creating an appealing visualization is vital. After all, it’s the key to making sense of all that data and transforming it into a format that’s understandable for everyone. 

Challenges in the role 

When dealing with so many variables, it is natural for hurdles, which can include misinterpretation and having too much information, to emerge. Many of these obstacles a data visualization analyst can experience involve the audiences’ perception of the visualization, including:

• Misinterpretation: If the visualization is not clear enough, the audience can misinterpret what you’re trying to convey. Make sure the information you want to get across is clear and easily understood.

• Too much information: Including too much information in your visualization can easily overwhelm and confuse your audience, potentially detracting from the information you’re communicating. 

• Lack of interest: This is something you should strive towards with your audience. Striking the right balance ensures your visualization is both engaging and informative without overwhelming your audience. 

Prepare for a data visualization analyst career path with Coursera

Data visualization analysis is an ever-developing career, with more businesses continuing to recognize their importance. Discover helpful tools to help you launch your career as a data visualization analyst on Coursera. For example, you might consider gaining a career certificate from IBM’s Data Analysis and Visualization Foundations Specialization. You can also focus on a particular tool with a specific program like the Microsoft Power BI Data Analyst Professional Certificate or Johns Hopkins University’s Data Visualization and Dashboarding with R Specialization, all available on Coursera.