Data Visualization: Definition, Benefits, and Examples

Data visualization is a powerful way for people, especially data professionals, to display data so that it can be interpreted easily. It helps tell a story with data by turning spreadsheets of numbers into stunning graphs and charts.

Learn about data visualization, including its definition, benefits, examples, types, and tools. If you decide you want to learn the skills to incorporate it into your job, you can also explore online courses you can do from anywhere.

What is data visualization?

Data visualization is the representation of information and data using charts, graphs, maps, and other visual tools. These visualizations allow us to easily understand any patterns, trends, or outliers in a data set.

Data visualization also makes data accessible to the general public or specific audiences without technical knowledge. For example, a government health agency might provide a map of vaccinated regions.

The purpose of data visualization is to help drive informed decision-making and to add colorful meaning to an otherwise bland database.

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Benefits of data visualization

Data visualization can be used in many contexts in nearly every field, like public policy, finance, marketing, retail, education, sports, history, and more. The benefits of data visualization include:

• Storytelling: People are drawn to colors and patterns in clothing, arts and culture, architecture, and more. Data is no different—colors and patterns allow us to visualize the story within the data.

• Accessibility: Information is shared in an accessible, easy-to-understand manner for a variety of audiences.

• Visualize relationships: It’s easier to spot the relationships and patterns within a data set when the information is presented in a graph or chart.

• Exploration: More accessible data means more opportunities to explore, collaborate, and inform actionable decisions.

Data visualization and big data

Companies collect “big data” and synthesize it into information. Data visualization helps portray significant insights—like a heat map to illustrate regions where individuals search for mental health assistance. To synthesize all that data, visualization software can be used in conjunction with data collecting software.

Data visualization tools

You can find plenty of data visualization tools out there to suit your needs. Before committing to one, consider researching whether you need an open-source site or could simply create a graph using Excel or Google Charts. The following are common data visualization tools that could suit your needs. 

• Tableau

• Google Charts

• Dundas BI

• Power BI

• JupyteR

• Infogram

• ChartBlocks

• D3.js

• FusionCharts

• Grafana

Get started with a free tool

No matter the field, using visual representations to illustrate data can be immensely powerful. Tableau has a free public tool that anyone can use to create stunning visualizations for a school project, non-profit, or small business. 

Types of data visualization

Visualizing data can be as simple as a bar graph or scatter plot but becomes powerful when analyzing, for example, the median age of the United States Congress vis-a-vis the median age of Americans. Common types of data visualizations are:

• Table: A table is data displayed in rows and columns, which can be easily created in a Word document or Excel spreadsheet.

• Chart or graph: Information is presented in tabular form with data displayed along an x and y axis, usually with bars, points, or lines, to represent data in comparison. An infographic is a special type of chart that combines visuals and words to illustrate the data.

• Gantt chart: A Gantt chart is a bar chart that portrays a timeline and tasks specifically used in project management.

• Pie chart: A pie chart divides data into percentages featured in “slices” of a pie, all adding up to 100 percent. 

• Geospatial visualization: Data is depicted in map form with shapes and colors that illustrate the relationship between specific locations, such as a choropleth or heat map.

• Dashboard: Data and visualizations are displayed, usually for business purposes, to help analysts understand and present data.

Data visualization examples

Using data visualization tools, different types of charts and graphs can be created to illustrate important data. A few examples of data visualization in the real world are:

• Data science: Data scientists and researchers have access to libraries using programming languages or tools such as Python or R, which they use to understand and identify patterns in data sets. Tools help these data professionals work more efficiently by coding research with colors, plots, lines, and shapes.

• Marketing: Tracking data such as web traffic and social media analytics can help marketers analyze how customers find their products and whether they are early adopters or more laggard buyers. Charts and graphs can synthesize data for marketers and stakeholders to better understand these trends. 

• Finance: Investors and advisors focused on buying and selling stocks, bonds, dividends, and other commodities will analyze the movement of prices over time to determine which are worth purchasing for short- or long-term periods. Line graphs help financial analysts visualize this data, toggling between months, years, and even decades.

• Health policy: Policymakers can use choropleth maps, which are divided by geographical area (nations, states, continents) by colors. They can, for example, use these maps to demonstrate the mortality rates of cancer or ebola in different parts of the world. 

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Jobs that use data visualization

From marketing to data analytics, data visualization is a skill that can be beneficial to many industries. Building your skills in data visualization can help in the following jobs:

• Data visualization analyst: As a data visualization analyst (or specialist), you’d be responsible for creating and editing visual content such as maps, charts, and infographics from large data sets. 

• Data visualization engineer: Data visualization engineers and developers are experts in both maneuvering data with SQL, as well as assisting product teams in creating user-friendly dashboards that enable storytelling.

• Data analyst: A data analyst collects, cleans, and interprets data sets to answer questions or solve business problems.

Data is everywhere. In creative roles such as graphic designer, content strategist, or social media specialist, data visualization expertise can help you solve challenging problems. You could create dashboards to track analytics as an email marketer or make infographics as a communications designer.

On the flip side, data professionals can benefit from data visualization skills to tell more impactful stories through data.

Read more: 5 Data Visualization Jobs (+ Ways to Build Your Skills Now)

Dive into data visualization

Data visualization can help you tell a story with data in a way that’s easier for your audience to understand. Learn the basics of data visualization with the University of California Davis’ Data Visualization with Tableau Specialization. You’ll leverage Tableau’s library of resources to learn best practices for data visualization and storytelling, learning from real-world and journalistic examples. Tableau is one of the most respected and accessible data visualization tools. 

To learn more about data visualization using Excel and Cognos Analytics, take a look at IBM’s Data Analysis and Visualization Foundations Specialization.