About the Book

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My Assessment

What to Expect

Recently, I finished reading ‘Storytelling with Data,’ a book written by someone with firsthand experience in creating and presenting data visualizations in a corporate setting. The book provides numerous working examples with graphs and a detailed thought process. Packed with examples, it clarifies best practices of data visualization, including the usage of text and pre-attentive attributes.

This book is a valuable resource for organizing your thoughts and gaining a basic understanding of the key features of graph building. Whether you have no experience or are a beginner, this book will undoubtedly set you on the path to creating decent dashboards and graphs.

The book is well-structured, and its simplicity in writing facilitates easy understanding. It emphasizes storytelling and offers advice on the use of graphs, colors, and more. Additionally, the book presents working examples and case studies, which are refreshing.

One of my favorite chapters focuses on storytelling, where the author excellently explains the importance of this skill. I couldn’t agree more with her insights. The author also provides some excellent references for further reading if you wish to explore this topic further. The book includes many practical pieces of advice to help structure your thought process.

I view storytelling as analogous to making pearl jewelry. Individual pearls represent facts, the string is the story, and choosing to design by placing pearls of different sizes makes the necklace unique.

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Your necklace could be simple with all the same size pearls, or it can be as delicate and intricate as the occasion demands.

What not to Expect

Reading this book alone will not make you the best dashboard or graph designer out there. However, it does provide valuable advice, introduces readers to numerous cognitive concepts, storytelling techniques, and practical tips. If you follow the guidance offered, it can elevate your output instantly. The next step is up to you — to seek out specific materials and continue practicing to develop your own craft.

My disagreement

I disagree with the author’s assessment of categorizing pie charts, donut charts, and others as ‘never to be used.’ I believe each of these has a time and place, including 3D charts. For example, if you’re building a fundraiser for children or pets and want to include a 3D or donut chart, I can see its usage. Even in a corporate setup, such as when building infographics for a department expansion party or another lighthearted occasion, these charts could be used wisely as interesting elements.

While I agree with the author and the general perspective out there about not using flashy colors and 3D graphs that are hard to interpret, and opting for charts like bar and line which people are trained to read and interpret easily, I don’t fully agree with the idea that these tools should be permanently removed from your toolkit.

Another point worth mentioning is that the book discusses cognitive load, Gestalt principles, iconic representation, and short- and long-term memory. To gain a more in-depth understanding and actually make use of these concepts, additional readings from other materials may be necessary, as the book only briefly touches on these topics.

Although I appreciate the author for mentioning these concepts, an interested reader may need to explore other resources to delve deeper into these subjects.

My final thoughts

The book is a light read with 10 chapters, which I was able to finish in 12–15 days, mostly reading one chapter a day. I would definitely recommend this book if you are interested in data visualization. It’s an easy and quick read.

Happy reading, book lovers!