Data Visualisation: A Handbook for Data Driven Design First Edition

I should begin this review with an admission of some bias. As a student in the MICA Information Visualization MPS program I was fortunate to have the author (Andy) as an instructor, and I was a fan of his website visualisingdata.com for some time prior. My fellow students and I — a mixed bag of designers, data wranglers, and the data curious — loved his course, soaking-up the practical wisdom and using it to reorient our approach to our work. I hoped this book would capture the substance of those lessons, and I wasn't disappointed.Andy fills a distinct and important niche in the sometimes overwhelming, multi-disciplinary realm of data visualization. He has built a portable, scalable mental framework to help both aspiring and practicing data visualizers navigate the dozens of decisions they will encounter in their work. One of Andy's strengths is his ability to walk the line between theory and practice. In the book, he calls dataviz a "game of decisions" and then, in his reassuring-but-methodical style, he prepares you to make sound choices when facing those tough, real-world decisions — whether they're related to data, story, or design. For me, the emphasis on process (chapters 2 through 5) is the most valuable part of this comprehensive and eminently useful book; the fundamental practices ("hidden thinking") that shape and steer great visualization work, much more than the latest whiz-bang technology.I would recommend this book to those who are new to data visualization as a solid primer and template for developing their work process, but also to working visualizers who want to get back to basics in order to strengthen their process, decision-making, and problem solving.

My Cred: I'm employed as a professional specifically for data visualization and I have read many books on the topic, from design to science, to practical stuff, to writing code, and then just theory.This resource is good for beginners and professionals. It does not contain code or technical how-tos (nor does it promise this), but it DOES promise to teach a method of design that is data-driven - and it delivers on this promise. When resources set themselves up with clear expectations and deliver, those resources get 5 star reviews from me.Part B I have found ESPECIALLY valuable in my time owning this as it goes over *ways to think* that can improve your visualization design process. Learning how to think about visualization design is quite hard, and is why I believe this book succeeds to meet the expectations it sets out.My second favorite part of this book is the short reference center in the middle (grey pages): This has a wide selection of helpful charts for different purposes, according to the shape and form of the data you are working with. I even encountered a couple charts I had never seen before!

Very clear and informative. This is a very good material for an undergraduate/graduate course. Straight to the point with focus on details. The only bad thing is that the kindle edition is not perfect (some images are bigger than the margins) but the printed version is flawless.

I got the online version, and it was extremely difficult to read. For a book that focuses on accessible visualizations, it struck me as odd that none of the visualizations in the book were interactive, or for that matter, legible.Other than that, the content of the book is good. I would just recommend getting the paperback format.

Among all the books I have read regarding Infographics and data presentation/design, this one provides the best mix of details and general overview.; not too much, not too little. I highly recommend.

Great Read. Really bice visuals. Delivers what it says it would.

Author loves himself more than the area where he supposed to be an expert. Instead of giving something exciting about the subject he provides kind of boring instructions how to make your work more efficient. Out of 350+ pages there are tons of water and common sense things which attract little attention. It looks like that the author tries to prove to himself how he smart he is instead of sharing something really meaningful with the audience. You'd better watching YouTube videos (for free!) from practicing experts, than spending time & money on that wastepaper.

Could become THE DataViz "textbook" for Academia.Incredible resource.Kudos & Congrats to the Author. Love It!