What Are the Top Data Visualization Techniques?

Key takeaways

• Charts, dashboards, graphs, treemaps, and infographics are among the top data visualization techniques.

• A geospatial map that helps demonstrate relationships between various locations on a map is a practical example of data visualization.

• Tableau, Power BI, and Google Sheets are examples of popular data visualization tools.

You can create and design data visualizations as a data scientist or analyst. Read on to discover more about data visualization techniques and the job roles that utilize them.

Afterward, if you’re ready to take the first step toward a career in data analysis, enroll in the Data Analysis and Visualization Foundations Specialization. Beginner-friendly, this program offers guidance on performing data wrangling, creating various types of charts and plots in Excel, using Cognos Analytics to generate interactive dashboards, and more.

What is data visualization used for?

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 challenging to understand, so visualization techniques help you display it in a way that is easier to work with. They make data clearer to analyze and report, and therefore more convenient for employees across an organization, regardless of their technical background.

Effective data visualization techniques

You can choose between data visualization techniques such as tables, graphs, and treemaps, based on the data you are working with, what you are using it for, and who you intend to share it with. Explore some popular data visualization techniques to understand how they help translate data into meaningful insights:

• 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 can 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 offers another way to understand 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 enables you to highlight relevant information to tell a story. You can use charts and graphs to demonstrate progress, highlight areas for improvement, and build credibility.

Who benefits from data visualization?

Data visualization has benefits common across industries and helps all professionals within an organization understand complex data. However, some professionals, such as data scientists and health care analysts, work closely with data visualization and get significant value from using it.

Data scientists and analysts

Median annual salary (BLS): $120,230 [1]

Job outlook: 35 percent [1]

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

Your primary task as a data scientist or analyst involves collecting, analyzing, and finding meaning from large volumes of data. You may also use visualization tools to help you present and report on data in a meaningful way.

Business executives

Median annual salary (BLS): $108,780 [2]

Job outlook: 5 percent [2]

Requirements: A bachelor’s or master’s degree in business or a major related to your area of work. Plus, 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

Median annual salary (BLS): $165,780 [3]

Job outlook: 6 percent [3]

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

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

Health care analysts

Median annual salary (BLS): $68,020 [4]

Job outlook: 16 percent [4]

Requirements: A 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.

Read more: Data Trends: Analytics, Governance, and More

Pros and cons of various data visualization techniques

Data visualization has several advantages alongside some limitations. Data visualization techniques allow 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

Creating effective data visualizations requires 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 can find a range of tools available, depending on the visualization you wish to create.

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

• Tableau

• Power BI

• Google Sheets

• D3

• Plotly

Check out our free resources on data analytics

Join Career Chat on LinkedIn for weekly updates on popular skills, certifications, and career-building advice. Discover more about data management and analytics with our other free digital resources:

• Watch on YouTube: The Future of Data Visualization: AI & Automation Trends

• Take a quiz: Which Data Analysis Course Should You Take? Find Out in 1 Minute

• Hear from an expert: 6 Questions with a Microsoft Data Analytics Leader

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