Resources
Back
featured Customer

Saved 100s of hours of manual processes when predicting game viewership when using Domo’s automated dataflow engine.

Watch the video
About
Back
Awards
Recognized as a Leader for
29 consecutive quarters
Spring 2025 Leader in Embedded BI, Analytics Platforms, Business Intelligence, and ELT Tools
Pricing

What Is Data Visualization? Key Benefits, Types, and How It Works

What is data visualization?

Data visualization is the graphical representation of information and data using visual elements like charts, graphs, maps, and dashboards. Its purpose is to transform raw data into an accessible and understandable format, making it easier to communicate insights such as relationships, trends, and patterns found during data analysis.

Our brains are naturally drawn to color and pattern, which is why visual representations are so effective. Instead of struggling to interpret large spreadsheets, stakeholders—regardless of technical expertise—can quickly grasp key takeaways and make informed decisions. Whether the goal is to spot outliers, track performance, or tell a compelling story, data visualization turns complex data into clear, engaging insights.

Common types of data visualizations

Charts Tables & Graphs Maps
Pie chart Highlight table Dot distribution map
Line chart Text table Heat map
Forecasting chart Timeline Treemap
Bubble chart Scatter plot Geographic map
Gantt chart Streamgraph
Bar chart Bullet graph
Area chart Wedge stack graph
Histogram Box plot
Waterfall chart
Funnel chart
Spider chart

Infographics
Infographics combine data and narrative in one location. They are useful for breaking down complex concepts and backing up those concepts with data points.

Dashboards
Dashboards can bring together multiple types of data visualizations into one interface. They enable anyone to track, analyze, and display data insights, and they can be customized to meet the needs and data governance requirements of individual organizations, departments, and users.

Why is data visualization important?

Organizations are gathering and storing more data than ever before. But, discovering data insights isn’t useful unless decision makers across organizations can understand them and apply them. Data visualization makes it easy for those without extensive data expertise to analyze large amounts of information and make data-driven decisions.

Data visualization is an important part of data democratization and the push to continually increase business intelligence. The better organizations understand their data, the better they can use it.

Benefits of data visualization

Data visualization plays a crucial role in transforming complex information into clear, actionable insights. By presenting data visually, organizations can make smarter, faster decisions and foster better collaboration across teams. Below are the key benefits in detail:

Faster Decision-Making

Visualizing insights makes data easier to understand in less time, enabling quick, informed decisions. This reduces the dependency on IT teams for data analysis and helps minimize project backlogs, ensuring businesses remain agile.

Higher Data Retention

When data is presented with engaging visuals, people are more likely to retain the information and recall key takeaways. This leads to more effective decision-making and actions based on the presented insights.

Improved Communication

Visual storytelling bridges communication gaps across departments, aligning everyone from data scientists and marketers to executives. Shared visuals create a common language, helping teams collaborate and strategize effectively.

Increased Operational Efficiency

Visualization tools make it easy to identify bottlenecks, performance gaps, and inefficiencies. By highlighting these areas, businesses can optimize workflows and improve overall productivity.

Cost Savings

By revealing inefficiencies and uncovering opportunities, data visualization simplifies process optimization. Organizations can streamline operations, reduce unnecessary spending, and allocate resources more effectively.

Data visualization is not just a tool—it’s a strategy that drives better understanding, alignment, and results across all levels of an organization.

How data visualization supports decision-making

Data visualization plays a crucial role in enabling effective business decisions. By transforming data into visuals, stakeholders can quickly detect anomalies, compare performance, and track KPIs in real time. Dashboards and charts make it easier to evaluate what’s working and what isn’t, helping organizations act decisively and confidently.

Whether it’s monitoring website traffic, comparing sales across regions, or identifying operational inefficiencies, data visualizations turn raw metrics into actionable insight.

How does data visualization work?

Data visualization may sound like simply choosing a few bright colors and a cool graph, but truly effective data visualization requires a balance between powerful visuals and clear data communication. A data visualization should have both strong analysis and strong storytelling.

The data visualization process starts with accurate data. Before you can create a graphic, you must review your data to be sure that information is correct and consistent.

Then, you need to consider your message and goal. What are you trying to visualize? What information do you want to communicate? You could be comparing data points, showing data distribution, visually displaying a specific structure, or trying to follow the connection between specific data points.

Next, think about your audience. How do they process visual information? How familiar are they with the data you will be sharing?

Remember, the key to great data visualization is often to choose the simplest approach. Avoid unnecessary visual elements like images, fonts, or colors that could clutter your chart or distract from the most important messages. Instead, use them wisely for emphasis.


Exploratory vs. Explanatory Visualizations

Data visualizations generally serve two distinct purposes: exploration and explanation. Both play crucial roles in analyzing and communicating data effectively, but they are designed for different audiences and goals.

Exploratory Visualizations

These are tools that allow analysts, data scientists, or teams to dig into datasets and uncover hidden patterns, trends, or relationships. They are highly interactive and flexible, encouraging experimentation and discovery. Users can filter, zoom, and manipulate the data to generate hypotheses or identify areas that need deeper investigation. For example, an exploratory visualization might be used during the early stages of data analysis to identify correlations or outliers.

Explanatory Visualizations

These are carefully crafted visualizations designed to communicate specific insights or findings to a broader audience, such as stakeholders, decision-makers, or the general public. The primary goal is to tell a clear and compelling story, ensuring the audience understands the key message at a glance. Explanatory visualizations are typically found in reports, presentations, and dashboards, where clarity and simplicity are critical. They often use annotations, consistent color schemes, and focused narratives to guide the viewer through the data.

Successful data strategies often combine both approaches. Exploratory visualizations empower teams to uncover insights, while explanatory visualizations ensure those insights are effectively communicated to drive informed decision-making. Together, they bridge the gap between discovery and storytelling, making data accessible and actionable for everyone involved.

What should I look for in data visualization tools?

There are many data visualization tools on the market with varying degrees of complexity and capability. Look for tools that make analytics accessible and interactive, easy to create, and easy to understand. Here are a few additional features to consider:

  • Simple interface. Choose a tool that will allow anyone, regardless of data expertise or coding and design ability, to create advanced visualizations.
  • Data governance. Choose a tool that makes sure the right person has access to the right data. Data visualization tools should enable self-service while maintaining security.
  • Suggestions. Features like Domo’s Analyzer tool look at your data and suggest a type of visualization to get you started. Then, you can refine your choices as you go along.
  • Alerts. Alerts can notify you and your team when goals are reached or when data indicates that issues need to be addressed. With Domo’s Alerts, you can track changes to your KPIs in real time, from any device. You can define your own alert criteria and be notified how and when you want.
  • Storytelling. In data visualization, storytelling is essential. With features like Domo Stories, you can combine cards, text, and images in a drag-and-drop dashboard to tell a powerful story about your data. You can even customize your page layouts to emphasize details or certain points and guide users through the data analysis.

How do businesses use data visualization?

Data visualization is useful for organizations of all sizes and all industries. Everyone needs a better way to make sense of their data. Here are a few ways businesses can use data visualization.

Understanding changes over time.

The relationship between data and time is one of the most basic forms of data storytelling. When organizations can see trends over periods of time, they can identify patterns and opportunities for improvement.

Recognizing frequency of events.

How often an event is happening is another essential piece of information for any organization. This could be how often customers are making purchases, how often donors are donating, or how often injuries occur on the job.

Identifying correlations.

Determining where relationships exist between circumstances and variables can help companies find patterns or effects they didn’t know existed. Recognizing how different business decisions impact each other can increase efficiency and overall business intelligence.

Categorizing customers.

Marketers can use data visualization to sort and classify customers based on the factors that are most important to their business objectives.

Managing projects.

Data visualizations like timelines and Gantt charts can help organizations manage complex projects and stay on deadline.

Discovering trends.

Using data visualization tools, organizations can pinpoint emerging market trends that can help them stay ahead of their competitors.

How will data visualization evolve in the future?

More and more, organizations will need to be able to customize data views and data access. Data visualization tools will make it increasingly simpler to do just that while aligning data visualizations to workflows for immediate action.

The industry will see businesses take advantage of not only dashboards, but also intelligent apps for unprecedented customization and data democratization.

Table of contents
Try Domo for yourself.
Try free
No items found.
Explore all