What is Data Visualization? Definition and Best Practices to Improve Visualization

Data visualization is the use of graphics such as charts, plots, infographics, and even animations to represent data. These visualizations break complex data relationships down and allow users to extract insights in an easy-to-understand manner.

Data visualization tools can be used for a variety of purposes and enables business users to leverage data for decision-making without relying on data teams. It is also used by management to communicate organizational structure and hierarchy, and data analysts and data scientists use it to discover and explain patterns and trends.

Why is data visualization important?

Data visualization is critical for businesses to quickly identify data trends, which would otherwise be time-consuming. Analysts can visualize concepts and new patterns thanks to the pictorial representation of data sets. As data volumes explode, making sense of the quintillion bytes of data is impossible without data proliferation, which includes data visualization.

Data is a critical part of every industry which is why understanding your data with the help of visualizations is important. Every company’s most valuable asset is its information. Through visualization, one can effectively capitalize on that information by making informed decisions.

In today’s world, companies are actively looking for talented individuals and teams who can bridge the gap between analysis and storytelling. Data visualization can help with that as it sits squarely between these two methods of leveraging information. 

Using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports because of the way the human brain processes information. Recent studies confirm the significance of visual learning, with 65 percent of the population being visual learners. Data visualization is a quick and easy way to convey information quickly – and you can experiment with the type of visualization to see what works best for viewers.

Data visualization has the potential to solve a wide range of business problems. With tools like HockeyStack, companies can reap transformative benefits in critical areas of operation such as marketing and revenue optimization. 

Some benefits of data visualization tools include: 

-Increased speed of decision making
-Identifying errors and inaccuracies in data quickly
-Optimizing and instantly retrieving data via tailor-made reports etc.

What are some types of data visualization?

According to research, we generate 2.5 quintillion bytes of data per day.While this is a staggering figure, it is only expected to rise as the Internet of Things (IoT) progresses. In fact, 90 percent of the world’s data was created in just the last two years!

With so much information at our disposal, it is critical to understand how to organize it into analyzable, actionable insights. 

This is where knowing the best ways to visualize your data comes in handy. Let’s take a look at some visualization types and screenshots from HockeyStack’s live demo that you can use:

• Bar Chart
  One of the most common data visualizations is the bar chart or bar graph. In bar charts, data represented in the form of a bar along two axes. You can even use a color-coding system and a legend instead of placing the category name next to its respective bar.
  
  
  
• Funnel A funnel shows how users move through a certain process. In the image below, the funnel narrows, indicating that less users move to the next stage.
  

• Histogram
  A histogram is the best graph to use when first investigating a continuous variable. The histogram calculates the probability of representation of any value of the continuous variable under study, which is critical if you want to make inferences and estimate population values based on sample results.
  
• Area Chart
  An area chart combines a line chart and a bar chart to show how quantities change over time. Data points are plotted and connected by line segments, similar to a line graph. In the image below, you can see the example of an area chart which shows us the monthly expansion revenue data and how it changes over time. 

Pro Tip: With HockeyStack you can visualize your data without connecting to a third party tool. Try HockeyStack’s live demo now!

Data visualization best practices

Given the significance and variety of visualizations, it’s critical to remember some best practices that might improve the way your data is represented.

Here are four best practices for data visualization to help you effectively visualize data and present it in an understandable and aesthetically pleasing manner.

• Identify your target audience
  
  Identifying who you’re visualizing the data for, i.e. the target audience, is the first step in effective data visualization and communication. This can assist you in tailoring your techniques and methods to a specific audience.
  
  Marketers, business executives, social media managers, entrepreneurs, educators, students, and non-designers are some examples of your potential target audience.
  
  To ensure that everyone is on the same page, you can create a visual to help identify and represent your target audience. Data visualization must be clear and understandable to the target audience in order for them to process information efficiently.
  
• Choose the right visual for your purpose
  
  You can choose the type of graph or chart that will most effectively and efficiently convey the important information in the dataset.
  
  As you can see from the following points, there are many different types of information that can be represented by various charts:
  

1. Tables can organize a lot of information, but they can also confuse users looking for high-level patterns. 
2. Line graphs depict the interaction of two or more variables by measuring variations or patterns over time. 
3. Area charts are similar to line graphs in that they shade the region beneath the line. 
4. Bar charts are used to compare the amounts and totals of various groups.
   

• Design to keep users engaged  The latest user experience (UX) trend is to combine user workflow experience with actionable insights, suggestions, predictions, and the best next steps to take for the task or decision at hand.  You can make the most of these visualizations by keeping good design principles in mind and sharing only information that is relevant.
  
• Format your visualizations for accessibility To improve overall readability of your visualized data, ensure consistency and clarity in your chart’s design elements, such as axis or grid lines. Another thing to keep in mind is to keep clutter and noise to a minimum in your visualizations. Because data visualization is all about effective communication, it’s critical that your visualizations don’t include any extraneous information that will draw attention away from the important details. 

Improve data visualization with HockeyStack

HockeyStack is a complete analytics and attribution solution for SaaS companies. HockeyStack unifies marketing, revenue, sales, and product data into a single dashboard that requires no coding, allowing you to gain visibility into operations and processes at your SaaS. ​​

HockeyStack allows you to visualize your data without the use of third-party visualization tools and create dashboards using templates. The set-up process only takes a few minutes and tracking is done via cookie-less script, allowing you to track each signup, click, and demo booking without worrying about violating privacy rules.

You can integrate HockeyStack with Stripe, Paddle, and Hubspot to create any dashboard you can imagine, using any sales, marketing, revenue, or product metrics.


Leveraging data visualizations can help you clearly and effectively communicate insights from your data. The best visualizations make data easy to understand at a glance.

Keeping these data visualization best practices in mind makes it easier to create visuals that are truly useful to their audience.