Essential Data Visualization Skills

Using data to discover insights about customers and improve decision-making throughout a business is important, but you also need data visualization skills, such as knowledge of design and certain visual tools, to convey this information effectively to clients and stakeholders. Data visualization is about telling the story of the data to your audience. You need the right skill set to accomplish this. 

Discover essential data visualization skills, design principles, visualization tools, related technical skills, and how to increase your abilities in this area.

Core competencies in data visualization

If your job involves working with and analyzing data, it’s a good idea to gain a solid understanding of the fundamental skills and visualization tools needed to present data visually. Discover some core competencies regarding data visualization.

Understanding design principles

When designing a visual for presenting the findings of your data, adhere to certain principles, such as simplicity, clarity, repetition, and symmetry. Explore some of these basic principles in more detail:

• Simplicity: Your goal is to present the insights from the data in a visual format that is easy for your audience to understand. To accomplish this, consider using only the information necessary to convey the meaning of the data. Use simple charts with minimal gridlines and labels while also refraining from incorporating too many decorative elements. 

• Clarity: If you are comparing, for example, artificial intelligence usage across industries, you might simplify the visualization of the information by using a basic color scheme and a bar graph rather than a complex 3-D chart. 

• Repetition: Present your findings using similar types of charts, colors, or shapes throughout a presentation. Repetition forms a connection between the elements of your presentation, which reminds your audience that a relationship exists within the data. 

• Symmetry: The human brain is attracted to symmetry, so when your visual presentation contains this principle, it helps your audience better understand the information. 

Knowledge of visualization tools

When piecing together a visual presentation to convey the findings of your data, a working knowledge of certain visualization tools, such as Tableau, Power BI, and Adobe Creative Suite, can be useful. Being able to effectively operate these tools allows you to create modern visual displays in an efficient manner. 

Ability to select the proper types of charts

Choosing the right visual aid to tell the story of your data is an important skill in the field of data visualization. When trying to determine the proper type of chart for presenting your information, consider if you are displaying the data as a comparison, a distribution, a composition, or a relationship.

• Comparison: Consider using a line graph or a bar graph.

• Distribution: If you have many data points, a histogram may be a good choice. If you only have two or three variables to show, a chart might be more effective.

• Composition: A column or an area chart may be effective in this case because you can show changes over time.

• Relationship: When trying to show a relationship within the data, a scatter or bubble plot tends to work well.

Technical skills

Although the ability to use data visualization tools, such as Tableau and Power BI, will likely be necessary, consider developing additional technical skills to increase your chances of success in data visualization. Explore acquiring the following skills:

Proficiency in programming languages

To expand your skill set in this discipline, you can learn programming languages, such as R and Python. These programming languages can assist you in converting big data into helpful graphics. You can use R to create scatter plots, box plots, and histograms of your data. People working in data science tend to use Python frequently, and in terms of data visualization, it offers several graphing libraries such as pandas visualization, Plotly, and seaborn. 

Familiarity with data manipulation libraries

Another data visualization skill you want to develop is an understanding of data manipulation libraries, which are tools for processing, cleaning, and analyzing data. A few of the most effective Python data manipulation libraries are pandas, NumPy, Dask, Polars, and PySpark. Using these libraries can make it easier for you to manipulate, analyze, and visualize your data.

Storytelling with data

For raw data to offer valuable insights, find the story within the data and then use visualization tools to tell it to your audience. By building a compelling narrative with the data, you can assist your organization in decision-making and drive growth. Take a look at the following components of how to tell a story with data:

Crafting narratives with visualizations

Typically, the foundation of your data’s story is a combination of three elements: data, narrative, and visualization. First, your data, which is the bedrock of the story, needs to be collected from reliable sources and thoroughly analyzed. Next, build your narrative, which is the detailed part of your story that explains the important findings within the data. The narrative functions as the binding element of a data’s story because it is the portion in which you reveal the connections within the data. Finally, use charts, graphs, and diagrams to visually convey your narrative, making the data’s story and its insights more accessible to your audience. Hopefully, these new insights will lead to improved decision-making. 

Presenting insights effectively

You can effectively present the insights from the data by following a few simple tips: Organize the data, know the goal of your story, create an outline for it, and identify the actions you would like your audience to take after hearing the story.

Analytical skills

A well-developed set of analytical skills can also help you to gather insights from the data before successfully presenting it visually. When working with data, you want to be able to identify patterns, understand data distributions, and conduct statistical analyses. Developing your analytical skills means you’re more likely to create accurate and reliable data visualizations, which allow for better storytelling.

Identifying key trends and patterns

Understanding how to work with data in order to identify patterns will likely make it easier for you to construct your visualizations. Make sure you have a solid grasp of the source data so you can spot trends in the information. These patterns and trends in the data are what you will use to build your visualizations.

Understanding data context

For your audience to understand the meaning behind your data, make sure to provide context for it. When telling the data’s story to your audience, provide a clear connection between the data points so viewers can more easily comprehend what the information means. This can help them when it comes time to make decisions. Providing context can be the difference between telling a superficial story with the data and telling a story that moves people to take action.

How to gain more data visualization skills

You have several options for increasing your data visualization skills. You can take courses or workshops to enhance your data storytelling techniques, making your presentations more captivating for the audience. You can also become a member of one of the various online communities that hold competitions in data visualization. These allow you to practice your skills and get feedback while learning from your peers. Other options for further improving your data visualization skills are to seek out videos and articles. Finally, you might consider earning a credential like IBM’s Data Analysis and Visualization Foundations Specialization, which covers how to analyze data using Excel and how to create visualizations and interactive dashboards with Cognos.

Putting your skills into practice

Members, in places such as the Tableau Community, develop and host challenges where you can use and practice your data visualization skills. You can apply your knowledge in this field to various topics and products. If you’re relatively new to data visualization, the Tableau Community offers projects for beginners that help you establish the foundational skills for this field. Finally, this community also offers projects focused on how to tell stories with data.

Explore data visualization skills on Coursera

With data continuing to become more important within the economy, developing essential data visualization skills, such as analysis and data storytelling, can help your career. Discover more about data visualization with Google’s Data Analytics Professional Certificate, where you’ll build skills in in-demand areas like data visualization and get AI training from Google experts.