Managing and comprehending data would be a much easier task if it were uniform and limited to fewer sources. Unfortunately, this isn’t the case. Meaningful data comes in a diverse range of unstructured sources and formats including, emails, system logs, web pages, customer transcripts, documents, slides, informal chats, and an exploding volume of rich media like HD images and video. 

With the enormous volumes of information available to us, CIOs must ensure they actively educate themselves based on this data to make informed decisions. Through the various types of data visualization, this is possible. This guide will help CIOs get the most out of their data through data visualizations and by exploring the various types of data visualizations to decipher which visualization may be most effective in achieving their unique goals. 

Data Visualization Fundamentals

The most critical part of understanding data through data visualization is identifying the question or questions you want the data to answer. For data visualization to be effective, you must start with a question and end with a narrative that offers a definitive answer.

Before beginning a data visualization project, you’ll want to follow these four fundamental steps to ensure that you are setting yourself up for success:

  1. Have a foundational understanding of the data you want to visualize. Because every project has unique requirements, your visualization should display the unique qualities of the data set it represents.
  2. Identify what type of information you want your visualization to communicate to your audience. Are you trying to show a relationship between two variables, or are you trying to show changes over time?
  3. Take the time to understand your audience and how they process visual information. Who is your audience? What are their goals when viewing a visualization? What will they learn? How will your audience use the piece? This will better inform what type of visualization would be best to communicate your data.
  4. Finally, choose the visual that will communicate your data in the best and simplest form for your audience.

By following these steps, you ensure that your data is not only approachable but straightforward and easy for your intended audience to comprehend. After all, making data easier to understand and analyze is the main goal for data visualization. Secondly, following these steps will ensure that you are mindful about choosing a visualization that best suits the story you want to convey and provide the audience with actionable insights.

So which visualizations should you use?

Data Visualization Categories

Modern types of data visualization allow CIOs, key decision-makers, to extend beyond the limitations of the basic charts and graphs created in Microsoft Excel. Instead, data visualizations use a variety of sophisticated visuals to display this information. Often, we can break down the various types of data visualization into five distinct categories:


Data visualizations in this category must be linear and one-dimensional. Temporal visualizations commonly include lines that either stand alone or overlap with each other, with a start and finish time. Popular temporal visualizations include scatter plots, timelines, and line graphs.


Data visualizations in this category are commonly those that organize groups within larger groups. Hierarchical visualizations are typically used to display clusters of information. Hierarchical visualizations include tree diagrams, ring charts, and sunburst diagrams.


Network visualizations communicate the correlation between datasets within a network. Matrix charts, node-link diagrams, word clouds, and alluvial diagrams are typical representations of network visualizations.


Multidimensional visualizations use two or more variables to create a 3D visualization made up of several concurrent layers and datasets. Standard multidimensional visualizations include scatter plots, Venn diagrams, pie charts, stacked bar graphs, and histograms.


Geospatial data visualizations refer to visualizations that concern themselves with overlaying maps with various data points (i.e., showing COVID vaccination rates in certain regions). Standard Geospatial visualizations include flow maps, density maps, cartograms, and heat maps are types of geospatial data visualizations.

Common Types of Data Visualization

Column chart

The most well-known way to visualize data, a column chart, helps demonstrate a comparison among different data sets. These visualizations can also track data sets over time. However, column charts are only suitable for small and medium-sized data sets.

Bar chart

Bar charts make comparing related data sets extremely easy. Bar chart visualizations are best used when highlighting change over time, comparing different categories, or examining parts of a whole. 

Line chart

Line charts excel at showing resulting data relative to a continuous variable – most often time or money. We can also use line charts to highlight trends, acceleration, deceleration, and volatility. These visualizations are best put to use when trying to understand trends, patterns, and fluctuations in your data, comparing different but related data sets with multiple series or making projections.

Scatter plot

A scatter plot demonstrates the connection between items based on two sets of variables. This type of visualization should highlight correlations within a large quantity of data, as they help identify outliers more effectively.

Pie chart

These charts are best suited for making part-to-whole comparisons with discrete or continuous data. They are most impactful when used with small data sets and can compare relative values, compare parts of a whole, or quickly scan metrics.

Funnel chart

Funnel charts enable decision-makers to visualize a linear process with sequential connected stages, with each stage representing a percentage of the total. These visualizations work great for anyone wanting to display a series of steps along with the completion rate for each.

Heat map

Heat maps display categorical data by using color intensity to represent values of geographic areas or data tables. Often, these visualizations are used to highlight the relationship between the two measures and provide additional rating information.


Used to compare data sets over an interval of time or show a distribution of data, a histogram is a combination of a vertical bar chart and a line chart. While similar to a bar graph, histograms only relate to one variable instead of two. 


Map visualizations are generally used when analyzing and displaying data related to geography and presenting it on a map. They allow decision-makers to visually see the distribution or proportion of data in each region. Use a map when geography is a critical part of the story you are trying to tell.

Area chart

Area charts are used to demonstrate a time-series relationship. Unlike line charts, they can also visually represent volume and almost always compare two or more categories. To visualize how various items stack up or contribute to the whole, use an area chart.

Word cloud chart

This visualization is excellent for those in charge of SEO. Word cloud charts display a large amount of text data and quickly help users perceive the most prominent text, making them ideal for keyword research.

Pivot table

A pivot table compiles, clarifies, and sums up information stored in other tables and spreadsheets, uncovering the most relevant insights. They are also used to create unweighted cross-tabulations quickly.

Data Visualization Benefits

The great thing about data visualization is that leaders can use them across an organization, implemented in many departments to track departmental initiatives, discover new insights, and boost decision-making power. For example, a sales team might leverage data visualization software to monitor an outreach campaign’s performance, tracking metrics like qualified leads, demos, free trials, and purchases. Data visualization tools also help data engineers and scientists track data sources and perform fundamental exploratory analysis of data sets before or after more detailed advanced studies. But data visualization can help organizations achieve much more than that. Below we highlight some of the key benefits that are inherent in data visualization. 

Faster decision making

As we’ve stated in previous blogs, visual information is much easier to comprehend than written information. Through data visualization to break down complex data, audiences can understand what is being communicated quickly, allowing business leaders across an enterprise to evaluate and interpret the data more effectively. Organizations that can quickly act on data gain a competitive advantage in the marketplace because of their ability to make informed decisions faster than the competition.

Identification of areas for improvement

With data visualization, organizations can see where their performance is above average and fall short. For example, a marketing team discovers that they receive X number of website visits for every X number of campaign emails sent. In that case, the team can create a data visualization to compare clicks per email to the total website traffic to set goals and act as a visual motivator to meet their traffic quota.

Productivity improvements

Studies have begun to show that using data visualization in meetings decreases their length by reducing the time it takes to identify patterns and understanding the data, resulting in a boost to overall productivity. 

Revenue growth

Revenue growth is one of the many benefits organizations that leverage data visualization experience. According to a global business study conducted by PwC, organizations that use data visualization are not only leaders in revenue growth, but they also plan to invest even more in data visualization in the coming years.

Trend identification

One of the most obvious benefits of data visualization is the ability to identify trends more quickly. This has given numerous leaders an advantage as they now have a greater awareness of their company’s performance. Data visualization emperors these leaders with the insight necessary to build upon favorable trends and reverse negative ones.

Final Takeaways

The list of use cases and benefits of data visualization can be infinite. Data visualization is a must for any organization that is looking to grow and capitalize on today’s consumer market at this stage in the game. At InterKnowlogy, we understand the vital role data visualization plays in a business’s success and its role in powering mission-critical decision-making. If your organization is ready to get the most out of its data, we would be happy to chat in more detail about how we can create your custom data visualization solution. Contact us at

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