Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations

Years ago in a development program I was asked to draw something that "represented me." Drawing upon all of my visual, artistic and creative skills ... I drew a single vertical line down the center of the flip chart page. If you can relate, then this book is for you. To be clear, this is not a beginner's guide, per se; many of the example visualizations in the book are quite sophisticated, although the author's use of them to illustrate design points are easy to understand and implement. The beauty of this book is in the author's immensely readable writing style, the system of thinking visually to build better charts that he lays out in the book, and the use of many (many!) examples to make his points. On p. 12 the author states "I hope this book will become a well-worn, dog-eared companion." After just a few weeks my copy is already in that state.

The best I've seen yet. This wide-ranging book, in addition to what most other books cover, adds two nifty frameworks that, between them capture the essence of what took me years of experience to master, Firstly, while most other books focus on design execution, Berinato adds the dimension of contextual awareness as an essential element of a good chart, and devotes considerable space to elaborating how to create contextually aware charts. Secondly,his "Four types" framework covers both data driven and conceptual charts, which are not usually treated as related. It also makes a clear distinction between exploratory and explanatory charts, emphasizing how their requirements differ, a distinction which usually goes unappreciated. Hence it unifies, expands and at the same time differentiates the topic of charts in a remarkably useful way."Good Charts" has the clarity of thinking that makes it points clearly and simply, without clutter and without oversimplifying - the signature of a master. Highly recommended.

Easy read and insightful. There are some good tips on how to go about the planning process and really making impactful charts. Seems to be more geared towards info graphic charts that are created and static rather than continuously updated. However most of the points still apply

Great examples, recaps, and just enough theory. Every discipline has its dogma; The author provides pragmatic techniques for individuals and teams to story-tell with data.

This was excellent for a business intelligence class. I used it to rapidly get an edge to my peers and my presentations showed a dramatic difference in being effective. The author included many practical stories that you could easily relate to. This book will help also help with your work presentations. Give it a read and keep it in your personal library.

Thoughtfully written. Probably not great for experienced professionals. A little outdated.

I have accumulated a collection of data visualization and analysis books over the years. Most of them have some interesting points but they're mostly regurgitating the same crap that isn't very useful in practice. This book is different. This is the only book I actually open up and reference regularly when I'm considering how to communicate information most effectively. I actually let an exec at my company borrow it and I never got it back so I just bought it again. Highly recommended.

I use this book as a guide for Data Visualization class, it provides great examples on different graphs and when to use which. While the content is very similar to other books on the subject, the way its written makes it easy to explain and integrate in to daily practice.

This book outlines a systematic approach not to find the 'right' visualization or graph, but to find the better way to present the information you have given the context of that information

I read multiple books about data visualization (by Edward Tufte, Alberto Cairo, Stephen Few, Cole Nussbaumer Knaflic, Jonathan Schwabish and other authors). Therefore, before buying a new unknown to me book I always ask myself a question – do I need one more dataviz book?I did not know I needed this book. But I am happy that I bought this book. Good Charts is an excellent book. It provides a brief overview of data visualization history and visual perception. And it explains how to build good charts. But it is not a bunch of strict rules. The book just helps you to ask right questions (including questions to yourself), to understand what type of data visualization you need, to sketch and to prototype, to ask more questions and to refine your data visualization for better persuasion, but not for manipulation. It helps you to present your work and it gives you a great advice about constant practicing. The book even teaches you about how to speak about bad charts (in social media) to make dataviz community more pleasant for all of us (dataviz professionals and newbies).Good Charts is nota manual, and it is not an impractical philosophy book. It is a data visualization thinking enabler and it is a guide on your way into the world of better charts. And Scott Berinato is a great coach.

The author does and excellent job laying out the various considerations that should be understood before mapping data (or a concept) into a graph. I really like the framework he provides to classify the purpose of the graph, and then to consider how best to use visuals to convey that message. I found after reading this book that I am much more critical of poor or mediocre graphs that, even when attractive, miss the mark in conveying a message. I highly recommend this book if you're looking for some practical tips and a strategy for becoming more effective at graphing.

Este es un libro muy recomendable; enseña las reglas de construcción de comunicación de datos a través de gráficas; un libro esencial para aquellos que estudien el diseño de información.

Un livre très clair (en anglais tout de même) sur les bonnes pratiques pour réaliser des graphes marquants. Les exemples sont généralement pris sur des aspects économiques (business), mais on comprend très bien comment se servir des remarques pour d'autres types de données. Les pages de résumé en fin de chaque chapitre sont particulièrement bienvenues.