How to Organize Your Thoughts About Data Visualization

Top 2 Data visualization Frameworks

Richard Warepam
3 min readApr 6, 2024


Photo by Myriam Jessier on Unsplash

As a data analyst, you’ve likely faced the challenge of transforming complex data into compelling visual narratives.

Have you ever wondered if there’s a more systematic way to organize your thoughts during this process?

This article introduces two powerful frameworks — the McCandless Method and Kaiser Fung’s Trifecta Checkup — that aim to solve this very problem.

These methods provide a structured approach to data visualization, helping you craft visuals that are not only aesthetically pleasing but also insightful and engaging.

Whether you’re a seasoned analyst or a beginner in the field, this article offers valuable insights to enhance your data storytelling skills. Let’s dive in and explore these methods.

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The McCandless Method Simplified

David McCandless, a renowned data journalist and information designer, has crafted a systematic approach for narrating data stories, known as the McCandless Method.

This method underscores the significance of clarity and storytelling in data visualization.

Here’s how you can utilize it: (Do all these steps using a notepad and a pen)

  1. Begin with the Big Picture: Start by pinpointing the broad, overarching ideas you aim to communicate.

Ask yourself, “what is the main story or insight your data uncovers?”

2. Anticipate Questions: Think about the potential queries your audience might have when they encounter your visualization.

Think, “What are the evident questions, and how can you address them proactively?”

3. State the Insight: Express the primary insight of your graphic in a clear manner.

Consider, “What should the audience learn from it?”

4. Support with Data: Reinforce the insight you’re showcasing with relevant data points.

Make sure the data you highlight corresponds with the narrative you’re constructing.

Simplifying Kaiser Fung’s Junk Charts Trifecta Checkup

Kaiser Fung’s framework, known as the Junk Charts Trifecta Checkup, offers a perspective for critiquing and conceptualizing data visualizations.

It revolves around three pivotal questions:

1. What is the Question?: Identify the objective of your visualization. What are you aiming to answer or explore with your data?

2. What does the Data say?: Make sure that the data you’re using is pertinent and accurately mirrors the question at hand.

3. What does the Visual say?: The visual elements should represent the data in a clear and succinct manner, directly addressing the question.

Wrapping Up Data Visualization

By intertwining these frameworks, you can craft a visualization that is not only visually appealing but also rich in substance and clarity.

Remember, the aim is “to guide your audience through a data story that is both engaging and insightful”.

With the McCandless Method and the Trifecta Checkup as your go-to framework, you’re well on your way to mastering the art of data visualization.

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Richard Warepam

Data Scientist & Writer | Google Certified Data Analyst | As a Mentor - Writes on Data Science and AI | My eBooks: