Have you ever seen a graph or another type of visual representation of data? They are one of the most popular methods of presenting statistical findings that can be comprehended by many.

Visualization can be used to process, show, and analyze data into recognizable patterns. This strategy demands less time and effort from the brain to digest the information than tabular data analysis does. In simple terms, people can relate better to visualized data. 

Data visualization must be adopted by all firms to achieve transformative results in their core functional areas. In this article, we’ll discuss what is data visualization, its purpose, and its importance to your business. We’ll take a look at the benefits of data visualization, the different types, and the best data visualization practices to keep in mind.


What Is Data Visualization?

Data visualization is the process of representing data or information in a graphical or pictorial manner, such as through charts, graphs, maps, and even animations. This could be used to find patterns, trends, and correlations in complex data sets as well as to make them easier to interpret. 

They assist us in categorizing and organizing data based on topics and themes, which makes it simpler to process and comprehend. Data visualization tools and technologies are essential in this age of big data to evaluate massive volumes of information and make data-driven choices. Additionally, it offers a great approach for workers or business owners to clearly explain facts to non-technical audiences.

What Is The Purpose Of Data Visualization?

Data visualization serves a rather obvious function. It is to present complex data in a clear, intuitive, and visually appealing format, making it easier for people to understand and interpret the data. 

  • Data visualization increases the effect of your communications on your target audiences and delivers the findings from data research in the most convincing way.
  • With the use of visualization, you can quickly and more effectively understand large volumes of data. It aids in better comprehending the data to assess its impact on the business and graphically conveys the information to both internal and external audiences.

Importance Of Data Visualization In Business

It's difficult to imagine a professional field that doesn't gain from making data simpler to comprehend. Understanding data has significance in every STEM (Science, Technology, Engineering, and Mathematics) sector, as well as in those of government, marketing, finance, history, service industries, consumer products, education, sports, and so forth. Name it.

Data visualization is important in business because it allows for the efficient communication of complex information. Decision-makers find it much easier to see trends, patterns, and insights that can guide strategic business choices when data is presented in a comprehensible way. 

Data visualization, in particular, uses visual data to convey information in a way that is accessible, quick, and efficient. This method can assist businesses in determining what has to be improved, what influences consumer contentment and discontent, and what to do with certain items (where should they go and who should they be sold to). Stakeholders, company owners, and decision-makers may anticipate sales volumes and future growth more accurately with the use of visualized data.

benefits of data visualization

What Are The Benefits Of Data Visualization?

Here are insights on the benefits of data visualization:

  • Identify Patterns and Trends: Data visualization reveals additional, previously undetectable patterns. These additional emergent qualities of the data can create fresh, worthwhile insights that were previously unknown. The data is given more significance through visualization, which also enables business users to spot links and trends. By examining these patterns, users can narrow their attention to particular data points that require attention and assess how important they are for the development of their organization.
  • Easy Comprehension: The use of data visualization makes it possible to extract important information from huge data sets. Particularly large quantities of data can be daunting and challenging to comprehend. This is made possible through data visualization, which makes the important data values obvious and simple to see. Everyone in the firm can easily comprehend and interpret it as a result.
  • Enhanced Effectiveness: It can take a lot of time and effort to sort through data the old-fashioned way. Businesses can now get insights considerably more quickly thanks to data visualization than they could before the invention of visualization tools.
  • Detection of Outliers and Anomalies: Visualization can make it easier to identify outliers and anomalies in data, which can be important for identifying errors or potential issues.
  • Aid In Storytelling: Data visualization can be used to tell a story and create compelling narratives that can help convey information to an audience.
  • Improved Communication: Visualizing data can make it easier for people to understand and interpret complex data.
different types of data visualization 

What Are The Different Types Of Data Visualization?

Probably the first thing that comes to mind when you think about data visualization is a straightforward bar graph or pie chart. Although they could be a crucial component of data visualization and a standard starting point for many data graphics, the proper visualization has to be combined with the right set of data. Simple graphs are merely the tip of the iceberg. There are many different visualization techniques available to show data in attractive and useful ways.

Here are a few types:

  • Pie charts and stacked bar charts are graphs that are segmented into pieces that represent the entirety of a subject. They offer a quick method to arrange data and assess how big each component is in relation to the others.
  • Tables: These are made up of rows and columns and are utilized to compare variables. Although tables may display a lot of data in an organized manner, they can also be overwhelming for consumers who are only searching for high-level trends.
  • Scatter plot is a little more sophisticated technique for data visualization. Scatter plots are a useful tool for examining the relationship between numerous sets of data and two variables.
  • Histograms: This graph represents the amount of data that falls inside a specific range by plotting a distribution of numbers using a bar chart (without gaps between the bars). An end user can quickly find outliers in a given dataset using this visual.
  • Line charts and area charts: These visuals, which are commonly used in predictive analytics, depict a succession of data points across time to demonstrate change in one or more quantities. While area charts link data points with line segments, stack variables on top of one another, and use color to differentiate between variables, line charts use lines to show these changes.
  • Treemaps, which show hierarchical data as a collection of nested shapes, often rectangles. Treemaps are excellent for examining the proportions between groups by their area size.
  • Heat maps: These graphical representations are useful for displaying behavioral data according to location. This might be a spot on a map or even a webpage.
  • An infographic is a representation of data using words and images. Often makes use of charts or diagrams.

Data Visualization Best Practices 

With so many tools for data visualization readily available, there has also been an increase in information visualization that is unproductive. Remember that the basic objective of data visualization is to make data more engaging, pertinent, and understandable to a wide range of audiences.

The following recommendations can help to make sure that your data visualization is clear and helpful:

  1. Know Your Audience(s): Make sure your data visualization meets the demands of the audience for which it is intended. Present the visualization to one or two members of your target audience if you're not sure whether it is clear. This will allow you to obtain feedback and make any necessary adjustments before presenting it to a larger group of people.
  2. Set The Context: It's crucial to provide the audience with a broad background explanation to help them understand why this particular data item is significant. Your audience must comprehend how current performance measures up to something concrete, such as a goal, benchmark, or other key performance indicators  (KPIs), to motivate them to take action.
  3. Choose An Effective Visual: For instance, line graphs effectively illustrate time series data whereas scatter plots show the relationship between two variables. Make sure the illustration helps the viewer comprehend your key point. 
  4. Utilize Color: Using color to map data is a simple but incredibly powerful method. As an illustration, you may decide to color-code an unusual point in your dataset red to make it stand out from other points. If you're keeping track of the weather, for instance, use red to denote hot and blue to denote cold.
  5. Don’t Distort Data: Users risk unintentionally distorting findings if they go overboard with their designs and data visualization charts. Pie charts, for instance, should always be 2D. Although 3D pie charts may appear more intriguing and perhaps attract more attention, the unpleasant outcome makes it more difficult to understand each percentage of the chart. Any good graph, including pie charts, shouldn't be difficult to understand.
  6. Keep It Simple: To draw the user's attention, you need to be very deliberate while adding more information to data visualization. Eliminate information that can divert your target audience from your data visualization to make it as impactful as possible.

Final Thoughts

Naturally, we tend to remember the things we see more than the things we hear. With this, it is imperative will incorporate data visualization into our everyday business. 

As we all know, data visualization is a powerful tool that allows individuals and organizations to effectively communicate complex data and insights. It also provides a clear and intuitive way to understand large amounts of information, identify patterns and trends, and make informed decisions. 

The benefits of data visualization are numerous and can greatly aid in the understanding, interpretation, and communication of data. Data is every company's lifeboat. Let Capella Solutions help visualize you lifeboat!

Rasheed Rabata

Is a solution and ROI-driven CTO, consultant, and system integrator with experience in deploying data integrations, Data Hubs, Master Data Management, Data Quality, and Data Warehousing solutions. He has a passion for solving complex data problems. His career experience showcases his drive to deliver software and timely solutions for business needs.