Getting Started with Data Visualization

Introduction

Today, data visualizations are ubiquitous. Some seek to inform, entertain, or persuade. In data science for social impact, we are particularly interested in data visualizations that reveal useful patterns that can improve effectiveness or efficiency..

Data visualization uses statistical graphics, plots, information graphics, and other tools to communicate clearly and efficiently. Many companies are realizing the value of data visualization, and there are many useful tools to choose from. One example: the most recent Slack and Tableau integrations that allow users to synthesize data and directly communicate to their audiences. Tableau has been building up a conversational interface that enables users to drill down into large datasets using natural language. Now, it’s allowing users to ask questions about their data—and share the answers—via Slack.

The use of data visualization has transformed digital communications. Early in the COVID-19 pandemic, data visualizations about the rise of cases, deaths, and recoveries were splashed across social media channels. Some were accurate and others misleading, showing the importance of developing a sound data visualization practice. Many organizations, including the World Health Organization (WHO), the Center for Disease Control (CDC), and local health agencies, used data visualization to communicate about the state of the pandemic.  

Data visualization provides a quick and effective way to communicate information in a universal manner using visual information. Other benefits of data visualization include:

• the ability to absorb information quickly, improve insights and make faster decisions;
• an increased understanding of the next steps that must be taken to improve the organization;
• an improved ability to maintain the audience’s interest with the information they can understand;
• an increased ability to act on findings quickly and, therefore, achieve success with greater speed and fewer mistakes and
• the capability of interactivity around data, allowing users to interpret data based on the dimensions they choose. 

It’s important to note that visualizations are only as good as the data you leverage to create them. When data is incorrect or faulty, it can lead to misleading visualizations or, worse, misleading insights. This, in turn, can have serious business and legal implications.

In this Guide

• Learn about resources to get started on data visualization projects.
• See tools that empower your team to design data visualizations.
• Tools and examples of great data visualizations to inspire your inner designer.
• Upskill yourself by learning about data visualization.

Conclusion

The resources above will help you with getting started with data storytelling through visualization in your organization. We also suggest reaching out to peer organizations, whose challenges and learning may provide direct and current examples of ways forward.  Please feel free to suggest any other guides you found helpful by contacting us and we may incorporate them.