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Data Visualization: Exploring and Explaining with Data
DATA VISUALIZATION: Exploring and Explaining with Data is designed to introduce best practices in data visualization to undergraduate and graduate students. This is one of the first books on data visualization designed for college courses. The book contains material on effective design, choice of chart type, effective use of color, how to both explore data visually, and how to explain concepts and results visually in a compelling way with data. The book explains both the "why" of data visualization and the "how." That is, the book provides lucid explanations of the guiding principles of data visualization through the use of interesting examples.
448 pages, Paperback
Published May 18, 2021
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Displaying 1 - 2 of 2 reviews
May 27, 2025
I recently completed reading this textbook as part of a graduate-level course on data visualization. This is a comprehensive textbook designed to teach students how to both explore data visually and communicate insights effectively. It is a bit more academic and a tougher read than a previous book I read and reviewed (and I still consider to be the gold standard) “Data Story” by Nancy Duarte (https://executingorder66.wordpress.co....) I did find that reading Duarte’s book before this one made it easier to digest. It is widely used in many graduate and upper-level undergraduate courses in data science, analytics, and business intelligence – for good reason.
Some of the core themes in this book include:
• Exploration vs. Explanation: The book distinguishes between using visuals to explore data (identify patterns, outliers, trends) and using visuals to explain findings to others.
• Design Principles: It emphasizes best practices in visual design, including clarity, simplicity, and the ethical use of visuals. I like how the book – and the course – focused first on the nature of visualization before diving into the tools. Like the principles in other great books on data visualization, it recommends to go analog at first when conceiving how you would like to see data visualized. Great examples, including the famous Ted Williams pitch/hit analysis, Menard’s March to Moscow,” and others were cited.
• Tool Integration: Practical instruction is provided for tools like Excel, Power BI, and Tableau, making it hands-on and industry-relevant.
• Chart Selection: Guidance is given on choosing the right chart type for different data stories—bar charts, scatter plots, heat maps, etc.
• Color and Layout: The book discusses how to use color effectively and avoid misleading representations (like . . . 3D pie charts).
• Storytelling with Data: It teaches how to structure a compelling narrative using data visuals, blending analytical rigor with communication skills.
The book is well-received in academic settings for several reasons:
• Pedagogical Strength: It balances theory and practice, making it suitable for both classroom instruction and self-study.
• Real-World Relevance: Case studies and examples are drawn from business, healthcare, and public policy, helping students see the practical impact of good visualization.
• Accessibility: Despite being rigorous, the writing is clear and approachable, which helps students from non-technical backgrounds.
• Tool Familiarity: Its focus on widely-used tools like Tableau and Power BI aligns with industry expectations, making it a strong preparatory resource for analytics careers
In my own day to day work, I have to take a lot of customer data and shape it to help drive features. The most important takeaway from my experience is the emphasis on “precise tracking and cleaning of data to achieve valuable insights,” especially in the context of visualization. Data quality can make or break the value of insights—an idea that aligns closely with the book’s emphasis on the integrity and clarity of visual communication.
Originally published here: https://executingorder66.wordpress.co...
Some of the core themes in this book include:
• Exploration vs. Explanation: The book distinguishes between using visuals to explore data (identify patterns, outliers, trends) and using visuals to explain findings to others.
• Design Principles: It emphasizes best practices in visual design, including clarity, simplicity, and the ethical use of visuals. I like how the book – and the course – focused first on the nature of visualization before diving into the tools. Like the principles in other great books on data visualization, it recommends to go analog at first when conceiving how you would like to see data visualized. Great examples, including the famous Ted Williams pitch/hit analysis, Menard’s March to Moscow,” and others were cited.
• Tool Integration: Practical instruction is provided for tools like Excel, Power BI, and Tableau, making it hands-on and industry-relevant.
• Chart Selection: Guidance is given on choosing the right chart type for different data stories—bar charts, scatter plots, heat maps, etc.
• Color and Layout: The book discusses how to use color effectively and avoid misleading representations (like . . . 3D pie charts).
• Storytelling with Data: It teaches how to structure a compelling narrative using data visuals, blending analytical rigor with communication skills.
The book is well-received in academic settings for several reasons:
• Pedagogical Strength: It balances theory and practice, making it suitable for both classroom instruction and self-study.
• Real-World Relevance: Case studies and examples are drawn from business, healthcare, and public policy, helping students see the practical impact of good visualization.
• Accessibility: Despite being rigorous, the writing is clear and approachable, which helps students from non-technical backgrounds.
• Tool Familiarity: Its focus on widely-used tools like Tableau and Power BI aligns with industry expectations, making it a strong preparatory resource for analytics careers
In my own day to day work, I have to take a lot of customer data and shape it to help drive features. The most important takeaway from my experience is the emphasis on “precise tracking and cleaning of data to achieve valuable insights,” especially in the context of visualization. Data quality can make or break the value of insights—an idea that aligns closely with the book’s emphasis on the integrity and clarity of visual communication.
Originally published here: https://executingorder66.wordpress.co...
June 23, 2025
As far as textbooks go it’s actually not bad!
Displaying 1 - 2 of 2 reviews