What Are the Top Data Visualization Techniques?

Data visualization is an effective way of turning complex data into something visual and accessible for all. Businesses use data to drive decisions. Often, this data is complex and difficult to understand as it is, so visualization techniques provide options for you to display this data in a way that is easier to work with. They make data clearer to analyze and report, and therefore more convenient for people in an organization who are not technically minded.

Discover the types of data visualization techniques and tools available, plus how these can support your business to translate and effectively use data. 

Effective data visualization techniques

Data visualization techniques can mean many things. The way you use visualizations to translate data will depend on the data you have, what you are using it for, and who you share it with. You’ll find a number of options, including:

Tables and charts: Charts and tables are simple data visualization tools that you're likely familiar with. Displaying data in rows or columns remains an effective data visualization method, offering a clear, easily understandable format that facilitates quick and accurate conclusions.

Graphs: Graphs allow you to plot variables that you can compare and track changes with. These are great for tracking variations across multiple factors, making it easier for you to monitor changes effectively.

Infographics: Infographics allow you to visualize a combination of data. You can include multiple visuals—such as graphs, charts, and symbols—as well as informational text that collectively tell a story.

Geospatial maps: You’ll use a geospatial map to demonstrate relationships between various locations on a map, which are represented by shapes and colors.

Treemaps: Treemaps help visualize hierarchical data, using rectangles of different sizes and colors to demonstrate volume and place in a hierarchy.

Dashboards: Dashboards allow you to view a range of data, presented in various ways, to support your understanding of a theme. For example, your dashboard may provide you with data about a marketing campaign and could contain several visual representations of various elements of the campaign, all in one place.

The importance and application of data visualization

Data visualization is important for any organization looking to make data more accessible and readable. Data visualization is useful in many ways:

Enhancing comprehension: Visualizing something is a way of understanding it. Data can be complex and not easy to comprehend unless you present it in a way that allows people to process the information quickly. Visualization tools allow you to use colors and shapes to highlight patterns and trends with little explanation required.

Facilitating decision-making: Data visualization effectively supports decision-making by using it to answer important questions. It helps you to show trends and patterns for consideration. 

Storytelling: Data visualization is an effective way of highlighting relevant information to tell a story. You can use charts and graphs to demonstrate progress, highlight areas for improvement, and for building credibility.

Who benefits from data visualization?

You’ll find data visualization across all industries and for the benefit of all professionals within an organization when it comes to understanding complex data. However, some professionals work closely with data visualization and get significant value from using it. 

Data scientists and analysts

Average annual salary (BLS): $108,020 [1]

Job outlook: 36 percent [1]

Requirements: A bachelor’s degree or master’s degree with a relevant major such as math, statistics, computer science, business, or engineering.

As a data scientist or analyst, you’ll collect, analyze, and find meaning from large volumes of data. You’ll use visualization tools to help you present and report on data in a meaningful way.

Business executives

Average annual salary (BLS): $103,840 [2]

Job outlook: 6 percent [2]

Requirements: Bachelor’s or master’s degree in business or a major related to your area of work. Extensive industry and management experience.

As a business executive, you are in charge of strategic management and oversight for the company you work for, including management of people, budgets, and goals. C-level staff use visualization tools to support data-driven decisions.

Marketing professionals

Average annual salary (BLS): $156,580 [3]

Job outlook: 8 percent [3]

Requirements: A bachelor’s degree in business, marketing, communications, or similar. 

As a marketing professional, you’ll use data to develop and deliver marketing campaigns to reach a target audience, build exposure, and sell products. In this field, you’ll rely heavily on data from market research, and you may use visualizations in campaigns. 

Health care analysts

Average annual salary (BLS): $62,9900 [4]

Job outlook: 16 percent [4]

Requirements: Bachelor’s degree in health informatics, data science, or similar. 

As a health care analyst, you make important decisions on how to deliver patient care, using data to find trends and patterns, while developing theories to reach goals. Often, this involves presenting data to decision-makers in a way that is easy to read and understand.  

Pros and cons of various data visualization techniques

Data visualization has several advantages alongside some limitations you’ll need to consider. As you’ll know from above, data visualization allows you to present data in a way that is easy to understand, making it accessible to anyone involved in decision-making, whether they are technical or not. It’s an excellent tool for storytelling, allowing you to pull out patterns, trends, and data that support your narrative.

In terms of limitations, it’s important that you select the right type of visualization tool for the data you want to represent. If you don’t, you can misinterpret data with your visual and tell a misleading story by oversimplifying data or by drawing meaningless correlations.

How to get started in data visualization

To create data visualizations, you’ll need excellent analytical skills, as well as experience and understanding of data visualization tools. How complex this process is depends on your data and whether you are creating a simple bar chart, or using software to create something more intuitive. Consider the following steps:

1. Understand your data: Check that your data is accurate and know what you want to find in your analysis.

2. Plan your data visualization: Decide on a visualization technique that works well with your data. This could be a chart, an infographic, or a treemap.

3. Choose your data visualization tool: You’ll find a range of tools available, depending on the visualization you wish to create.

In order to achieve number three, you’ll want to learn about different data visualization software and tools. You might consider learning the following:

• Tableau

• Power BI

• Google Spreadsheets

• D3

• Plotly

Enhancing your data visualization technique skills on Coursera

Learning data visualization techniques allows you to transform complex data into clear, accessible, and visually appealing presentations. Many industries and professionals use data visualization, so it is a useful skill to have. If you’d like to learn more about turning your data into visualizations, you might check out the Google Data Analytics Professional Certificate. You can also choose a course that focuses on specific tools that you’ll use when taking on data visualization, such as the Microsoft Power BI Data Analyst Professional Certificate.