Data Visualization

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What is data visualization?

Data visualization is a broad term for any visual representation of data. It can include formats like charts, graphs, or dashboards. The goal of data visualization is to make it easy to communicate insights like relationships, trends, and patterns found during data analysis to stakeholders regardless of their data expertise.

As human beings, our eyes and our brains are drawn to things like colors and patterns. That’s why we live in a visually-driven world. Large spreadsheets of data are hard to understand. Data visualization presents that same information in a way that grabs and keeps viewers’ interests and tells a story.


Common types of data visualizations


  • Pie chart
  • Line chart
  • Forecasting chart
  • Bubble chart
  • Gantt chart
  • Bar chart
  • Area chart
  • Histogram
  • Waterfall chart
  • Funnel chart
  • Spider chart


  • Highlight table
  • Text table
  • Graphs
  • Timeline
  • Scatter plot
  • Streamgraph
  • Bullet graph
  • Wedge stack graph
  • Box plot


  • Dot distribution map
  • Heat map
  • Treemap
  • Geographic map

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 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 can benefit organizations in a variety of ways including:

  • Less time spent making decisions. Visually summing up data insights makes it simpler to share important findings with more people and accelerates the decision-making process. Accessible data visualization tools can eliminate IT backlog.
  • Increased data retention. When individuals have a visual accompanying data insights, they remember key takeaways more effectively.
  • Better transparency and understanding. Data visualization enables everyone from data scientists to marketing specialists to the C-suite to understand key concepts equally.

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.


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.



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