Data Visualization Techniques

ONPASSIVE

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12 May 2022
6 Min read

The Most Effective Data Visualization Techniques For Your Business

Data visualization is the visual representation of numerical data using graphs, charts, and maps. It is vital in interpreting large amounts of data, and adhering to specific data visualization best practices is critical.

Visualizing your data using various methods will help you become a more effective communicator. Data visualization is a helpful way of curating your data for many industries, from marketing to finance.

Anyway, some specific guidelines to follow can better represent your data and the effective communication you’re attempting to convey. Here are some of the best practices for data visualization to help you effectively visualize data and present it in an understandable and aesthetically pleasing manner.

What Is Data Visualization?

Data visualization is defined as “information that has been abstracted in some schematic form, including attributes or variables for information units.” In other words, it is a consistent method of visually communicating quantitative data. The data can be represented in various ways, depending on its attributes, such as a line graph, bar chart, pie chart, scatter plot, or map.

Graphic designers must follow data visualization best practices and visually present a data set. Data visualizations should be informative, visually appealing, and never deceptive. Developing a cohesive format is critical when working with massive data sets to create practical and visually appealing visualizations.

The Best Data Visualization Practices For Your Business

As previously stated, having the correct data is only half the battle. It is equally important to present it to understand, providing a space to convert their data into actionable visuals. Here are some critical practices businesses must adhere to when developing data visualization dashboards in collaboration with their data analytics service provider.

1. Understand The Goal Of The Process

Before you begin putting data into a visualization tool, it is critical to understand the process’s goal. If your stakeholders want to see the performance of your campaign, you won’t show them data about the tools you invested in or the task list of the agency you hired for the campaign. You will need to adjust what you show in the data based on your audience and what you want them to do next.

2. Addressing The Audience

While designing your data visuals, it’s crucial to answer the below-mentioned questions. 

  • Who is going to consume the data?
  • What challenges do they face?
  • What metrics or goals matter to the audience?
  • What decision do I want my audience to take?

The answers will help you collate the data points regarding the interest of your targeted audience. 

3. Show The KPIs

The ultimate goal of converting data points into visuals is to derive actionable insights. And the only way to do so would be to compare the data to the Key Performance Indicators (KPIs). Assume your goal was to increase the number of leads for your ABC service. You’d need to look at the various KPIs like traffic source, lead quality, etc.

4. Providing a Context

Data visualization is most useful when it demonstrates the relationship between datasets and their overall impact. While storytelling is not a must-have data visualization best practice, it is recommended. It helps with the following.

  • Inspiring action
  • Influencing the decision

5. The Data Should Be Readable

Ensuring clarity and consistency in the design goes a long way. The data presentation should be a healthy mix of visuals and text, with the text supporting the visuals as needed and the visuals well placed.

Another factor to consider is clutter reduction. Because the entire purpose of data visualization is to make data easier to communicate, the images must contain no unnecessary information or suffer from information overload.

6. Make Use Of Colors

Just because you’re working with data doesn’t mean your visuals have to be black and white. Using various color combinations can aid in representing various aspects or trajectories of your business journeys. Consider going back to your brand design guidelines and working with your brand colors when deciding which color or color combination to use.

7. Hierarchy Is Most Important

One of the fundamental concepts of data visualization is the hierarchy. It is the only thing that users understand intuitively, so it is up to data visualizers to use them optimally.

As you might expect, hierarchy entails placing the most critical information on top and downward in almost the least essential’ fashion.

8. Ensure The Designs Are Responsive

Responsive design is an approach in which pages display well regardless of the viewed device. The design automatically adapts to different screen sizes, making it easier for the end-user to read and digest the content.

The Bottom Line

Extensive dataset processing, analysis, and visualization have become critical factors in informing business intelligence decisions and determining the tangent of all professional activities and operations. Data visualizations inform, describe, and persuade marketing to sales and business development.

Using the best data visualization practices can make all the difference. By following the outlined guidelines, you can ensure that your data visualizations are always legible, convincing, and compelling.

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