Opens in a new tab
Plans & PricingSignup for FreeGet a demo
data-visualization

11 Key Principles of Effective Data Visualization

Telmo Silvaon June 12, 2018
Last updated on August 7, 2025

“We are overwhelmed by information, not because there is too much, but because we haven’t learned how to tame it,” per Stephen Few, well-known authority on data visualization.

Stephen Few, along with Edward Tufte, another prolific expert on the topic, have been providing thoughtful dialog on the worth of data visualization long before the explosion of data visualization within business intelligence (BI) tools. Nonetheless, their insights are widely considered best practices, even for data visualization in BI dashboards.

Endless possibilities for combining disparate data sets previously deemed too costly and time-intensive to tackle, now exist via comprehensive BI tools that enable you to create simple dashboards. The challenge is selecting a tool that provides clear value in an easily understandable format once all that data is merged.

Enter data visualization. Data visualization makes sense of rows and columns of data by representing it in charts and graphs that are much more easily digested. The way in which the data is visualized, however, makes a significant difference. Some data visualization outputs are still difficult to translate, causing vague or unclear takeaways and delays in decision-making.

Key Principles of Effective Data Visualization

The list below is a summary of the core concepts that make data visualization most useful, as identified by Few and Tufte.

  • Clarify – set a clear objective that people care about
  • Simplify – present only the visualization style that is most appropriate for the type of data being analyzed
  • Compare – display side-by-side comparisons for easy absorption
  • Attend – draw the viewer’s attention to the important/relevant data
  • Explore – create visuals that leads the viewer to discover new things, not simply answer a specific question
  • View Data Diversely – enable multiple views of the same data to discover various insights
  • Ask Why – question why something is happening, don’t simply note that it is happening
  • Be Skeptical – encourage more question-asking vs. accepting the simple answer provided by the initial query
  • Respond – share the data you uncover to gain alternate perspectives and build collaboration
  • Detail – make large data sets coherent and reveal data at several levels of detail
  • Validate – data visualization graphs should speak for themselves but also provide access to backup information and raw data as proof points

The most productive BI tools cause you to think about the meaning of the data you’re looking at and not focus on the tool, mechanics, images, or anything other than the information at hand.

ClicData takes data visualization seriously and invests in significant research efforts to ensure our BI dashboard templates and reports contain the most effective, easily consumable outputs possible. Our goal is not only to enable consolidation of disparate data stores but also to provide the data analysis you need to take action and improve your business’ bottom line. Request a professional BI consultation overview today.

Table of Contents

Summarize this content with AI

Other Blogs

AI Readiness Assessment For SMBs: Which AI Wave Is Your Team Actually Operating In

Agentic AI is the loudest topic in data and analytics, and if your leadership has started asking where your team stands, a shrug is no longer an acceptable answer. BARC's…

The Most Trusted ETL Tools by Data Engineers

Ask ten data engineers to name the most trusted ETL tools and you'll get a short list of products followed by a much longer list of caveats. This guide covers…

Why AI Pilots Stall Before the Model is Even the Problem

Most AI pilots never get cancelled. They demo well in the spring, pick up a second round of scope over the summer, and by autumn the two people who built…
All articles
This site is registered on wpml.org as a development site. Switch to a production site key to remove this banner.