What is information visualization?
Information visualization is the practice of representing data in a meaningful, visual way that users can interpret and easily comprehend. This includes data visualizations and dashboards. Information visualization is an effective way to share insights in a digestible format for non-experts. It usually shows relevant connections in the data and allows decision-makers to more easily draw conclusions and act in an informed way.
Information visualizations are often created with an audience in mind and designed to display certain important information that they need to understand. With an idea of how the visualization will be used, the visualization’s designer can determine the best format to organize the information and which visual elements to employ. At its core, information visualization is data storytelling using visual techniques.
Information visualization is increasingly popular today with advanced tools and technologies that allow for interactive features so that users can manipulate and play around with the data in real time. This allows non-technical users to investigate topics of interest from different perspectives and discover insights in the data with ease.
Information visualization vs. data visualization
A common question for many people is what is the difference between information and data visualization? While data visualizations are a representation of raw data, information visualizations represent the data visually in the context of business logic. It’s similar to asking what the difference between information and data is. Information is data with meaning attached to it. Both are valuable tools for representing data but information visualizations usually include more of a story around the data instead of a purely quantitative representation. Furthermore, not all information visualizations include data points, for example process visualizations, but most do. It is important to note that the distinction between the two is often blurred and many people use the terms interchangeably.
Types of information visualization
Information visualization tools can help users compare different values, show the bigger picture, track trends in the data, and understand different relationships between variables. The following visualization formats are most commonly used for these purposes:
- Column chart
- Bar graph
- Network graph
- Stacked bar graph
- Line chart
- Pie chart
- Scatter plot or 3D scatter plot
- Box plot
- Bubble chart
- Dual-axis chart
- Stream graph
- Sankey diagram
- Chord diagram
- Choropleth map
- Hex map
- Voronoi polygon diagram
- Ridgeline plot
- Interactive decision tree
- Tree map
- Circle packing
- Violin plot
- Real-time tracker
Why is information visualization important?
Almost everyone within modern organizations is demanding access to data, making the representation of that data in an easy-to-understand format even more important. Business users need a way to interpret data and interact with it in an intuitive way. Information visualization tools help these decision-makers navigate the data with less difficulty and therefore deliver value to the entire organization.
Information visualization is a key skill today as more companies look to digitally transform and make data a key asset across the organization. With ever-growing volumes of data, being able to present data in a meaningful way for others to understand has become crucial for a business to remain competitive. Information visualization turns data into actionable insights.
Use cases for information visualization
Information visualization is designed to assist users in understanding data. It can be used for the following purposes:
Presenting Information: Information visualizations are most commonly used to present information for others’ understanding and to persuade group members to act a certain way. A visual representation clearly shows the presenter’s argument and sometimes explains a concept better than a lengthy conversation could. Information visualization simplifies the complex and can prove useful in communicating information that may be otherwise too difficult to explain. However, it’s important to remain ethical in how you use the presentation of data to persuade others.
Data Exploration: Non-data experts can use interactive information visualizations to explore data on their own. This helps to democratize access to the data by allowing users to ask questions of the data on their own and get the answers faster without waiting for data experts. Through exploration, users are able to locate relationships that may exist within the data and make better decisions informed by the data. It may also spark a new idea or new thoughts on a concept, encouraging creativity and looking at data from different perspectives.
Idea Confirmation: Instead of relying on gut instincts or guesswork, users can confirm their “hunches” with reliable information in a visual manner. Information visualization can confirm previous understandings and track relationships in the data as they change over time. It can support decisions with careful analysis and reasoning that goes beyond supposition. Information visualization may even help users see previously otherwise unseen points in the data.
Information visualization examples
The following are some examples of different application of information visualization across different industries:
- Scientific studies
- Data mining
- Digital libraries
- Market research
- Crime mapping
- Policy modeling
- Financial analysis
What makes an information visualization successful?
Information visualization is an art and therefore relies on the following aspects of design:
- The subject matter: information or data being represented
- The story: the concept being portrayed in the visualization
- The goal: meeting the purpose with the right visualization
- The visual: using key elements of structure and design
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