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What is Data Visualization?

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Especially in the world of big data, you can’t always see everything data communicates through a database or spreadsheet. Even the most experienced data professionals can spend days combing through a database for insights, catching many important details but missing several other patterns or big-picture connections.

Data visualization is one of the most important solutions for finding and displaying key data insights. The practice involves pulling data from a database, either manually or via a data visualization tool, and creating a graph or chart that best displays all of the relationships, results, and trends found within the data set.

See below to learn more about how data visualization impacts data-driven businesses and what tools can help you get started with captivating data visuals.

More on Data Visualization

See more: What is Statistical Data Analysis?

Data visualization features

No matter what type of data you’re trying to visualize, these are some of the key features of data visualization:


Depending on the types of data you’re working with and the audience you expect to understand the data, you’ll want to choose a different visualization to communicate that information:

  • Charts
  • Tables
  • Graphs
  • Maps
  • Infographics
  • Dashboards

If you want to get more specific or creative in visualizing your data, these are some other popular visualization formats:

Gantt Chart Example of Data Visualization
This is a Gantt chart, a common type of data visualization for illustrating project schedules and dependencies on a timeline.
  • Heatmap
  • Treemap
  • Timeline
  • Word cloud
  • Dot distribution map
  • Gantt chart


Cardinality is a feature of data that comments on its uniqueness, specifically how many unique data points can be found in a database column. High cardinality is found in columns that focus on highly distributed values, such as social security numbers or birth dates. Low cardinality occurs when you find many repeated values in a column, like ages of students in a classroom or genders in a sample population. A low or high cardinality score will help you to determine what visualization best represents the data.


Correlations are the connections that data visualizations help you to see among seemingly disparate points of data. Graphs and line charts are particularly useful data visualizations for discovering correlations in a large data set.


Dashboards are not only a type of data visualization, but also a great tool for aggregating several data visualizations in one place. Major data visualization software providers offer a robust dashboard that you can customize to your specific needs.

See more: Qualitative vs. Quantitative Data

Benefits of data visualization

Basic database management and data analysis can provide you with a lot of insight, but non-visual practices can only make your data so digestible. 

Here are several reasons why businesses rely on data visualization to draw valuable insights from their data:

Quick understanding of meaning and patterns

Databases and spreadsheets might contain all of the information needed to draw conclusions about data, but those conclusions aren’t as readily apparent or memorable as data that has been visualized. Data visualization helps you to quickly discover and comprehend the most important information and patterns from a data set.

Data accessibility for non-data professionals

Data visualization simplifies complicated data points and concepts into visuals that non-data professionals, stakeholders, and external viewers can easily digest and understand, making the data more widely accessible. 

Business intelligence and competitive analysis

Since data visualization can illustrate key connections and trends in your data, the practice plays a large role in business intelligence. You can decipher what’s happening with your company’s KPIs and how they compare to your competitors, which gives you a competitive edge and a strategy for improvement.

Breaking down big data

Big data is never easy to digest. Data visualization tools can help you absorb all of this data and create summary visuals that provide insight, without requiring your team to dig through vast volumes of data for analysis.

Data visualization use cases

Since data visualization comes in so many different forms, you can use that data in a broad range of reports and presentations for a variety of audiences. 

Here are a couple of ways users have worked with data visualization tools to advance their data practices:

“I really like the dashboard preparation function of Power BI. I also really like the automation of a major portion of my work with the help of this tool. Being a developer I prepare charts and reports almost daily, I generally use Excel, Pdf, and CSV files. Power BI helps me to do things faster by automating several aspects of report/chart development and sharing.” -Analyst in the health care industry, review of Microsoft Power BI at Gartner Peer Insights 

“Tableau is my favourite data exploration and prep tool because of its rich visualisation capabilities and modern interface. It is my little get away from Pandas & Python and when I don’t want to fiddle too much with code as it offers a point & click, drag & drop environment and experience. Tableau is like excel on steroids. If you have used excel before you will be comfortable with Tableau’s environment. Certain workflows are similar especially when you are already used to working with MS Excel Pivot tables…Tableau’s intuitive interface and tools allow me to quickly draft capturing presentations for management and stakeholders with very little effort. And did I mention the interface is aesthetically pleasing?” -Database admin in monitoring services market, review of Tableau at Gartner Peer Insights

Data visualization market

The global data visualization market hit $8.85 billion in 2019, and since then, a compound annual growth rate of 10.2% has been forecast to result in a $19.2 billion market by 2027, according to Fortune Business Insights

Much of this growth has been attributed to growing interests in business intelligence, especially as data visualization insights have benefited health care, the public sector, and other businesses during the COVID-19 pandemic.

Data visualization software makers

Regardless of your industry and the types of data that you want to visualize, a data visualization tool can help your organization make sense of sprawling data sets and databases. 

Some of the top providers are below, and you can also take a look at this data visualization software selection tool from TechnologyAdvice for more guidance in your selection process.

  • Tableau
  • Sisense
  • Google Charts
  • Microsoft Power BI
  • Qlik
  • Adaptive Insights
  • Domo
  • Data Wrapper
  • Visually
  • Chartblocks
  • Xplenty
  • SAS Visual Analytics
  • Zoho Analytics
  • SAP BusinessObjects
  • IBM Cognos Analytics

See more: Best Data Modeling Tools & Software 2021

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