What do you think?
Rate this book
Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations
Dataviz—the new language of business
A good visualization can communicate the nature and potential impact of information and ideas more powerfully than any other form of communication.
For a long time “dataviz” was left to specialists—data scientists and professional designers. No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could.
What’s more, building good charts is quickly becoming a need-to-have skill for managers. If you’re not doing it, other managers are, and they’re getting noticed for it and getting credit for contributing to your company’s success.
In Good Charts , dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. Dataviz today is where spreadsheets and word processors were in the early 1980s—on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping.
This book is much more than a set of static rules for making visualizations. It taps into both well-established and cutting-edge research in visual perception and neuroscience, as well as the emerging field of visualization science, to explore why good charts (and bad ones) create “feelings behind our eyes.” Along the way, Berinato also includes many engaging vignettes of dataviz pros, illustrating the ideas in practice.
Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.
A good visualization can communicate the nature and potential impact of information and ideas more powerfully than any other form of communication.
For a long time “dataviz” was left to specialists—data scientists and professional designers. No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could.
What’s more, building good charts is quickly becoming a need-to-have skill for managers. If you’re not doing it, other managers are, and they’re getting noticed for it and getting credit for contributing to your company’s success.
In Good Charts , dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. Dataviz today is where spreadsheets and word processors were in the early 1980s—on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping.
This book is much more than a set of static rules for making visualizations. It taps into both well-established and cutting-edge research in visual perception and neuroscience, as well as the emerging field of visualization science, to explore why good charts (and bad ones) create “feelings behind our eyes.” Along the way, Berinato also includes many engaging vignettes of dataviz pros, illustrating the ideas in practice.
Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.
264 pages, Paperback
First published May 17, 2016
370 people are currently reading
2179 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 30 of 78 reviews
February 9, 2016
If you know me, you know that I'm a bit of a data nerd. Actually, who am I kidding? A BIG data nerd. So naturally I was absolutely thrilled when I got my hands on an advanced copy of Scott Berinato's Good Charts.
Let me start off by saying that this book is absolutely stunning. I know that you shouldn't judge a book by its cover, but because this is a book on data visualization, there needs to be some stellar imagery and examples-- and Good Charts did not disappoint. I was so inspired by just looking at all of the different charts and graphs throughout the book!
The content was also phenomenal. Berinato breaks down data visualization down to its basic components, serving as a starting point for beginners and a refresher for old pros. I'm somewhere in the middle, so his tips and tricks for making data appealing through visuals was a bit of both!
I'm not giving this book a full 5/5 stars because I thought it was a bit too drawn out. While I did enjoy the book, I found some of it to be a bit repetitive. This might be helpful for complete beginners, but I wasn't too captivated in these moments.
Note: I was given an advanced readers copy of this book by the publisher in exchange for an honest review.
Let me start off by saying that this book is absolutely stunning. I know that you shouldn't judge a book by its cover, but because this is a book on data visualization, there needs to be some stellar imagery and examples-- and Good Charts did not disappoint. I was so inspired by just looking at all of the different charts and graphs throughout the book!
The content was also phenomenal. Berinato breaks down data visualization down to its basic components, serving as a starting point for beginners and a refresher for old pros. I'm somewhere in the middle, so his tips and tricks for making data appealing through visuals was a bit of both!
I'm not giving this book a full 5/5 stars because I thought it was a bit too drawn out. While I did enjoy the book, I found some of it to be a bit repetitive. This might be helpful for complete beginners, but I wasn't too captivated in these moments.
Note: I was given an advanced readers copy of this book by the publisher in exchange for an honest review.
October 1, 2016
Pie charts won't cut it anymore. If you're trying to get funding for your project, impress your boss, or get a promotion, you need to up your data visualization skills.
This book has everything you need to do just that. Berinato breaks down the entire process, providing a step-by-step plan to create incredibly effective visualizations that will help you achieve your goals. He starts from the very basics, explaining what makes a good chart, what elements you should include, what to leave out, and how to present your data for maximum impact.
But Berinato doesn't leave you hanging there. Once the chart is complete, he shows you how to present it to your audience to achieve a positive outcome. But the most interesting section was the ethical one and whether you should manipulate the data in your favour.
Unfortunately, I read an advanced digital copy that had the graphics all messed up. Rather than enhance the content, it just confused me. If you're interested in this book, definitely pick up an old-school, physical copy.
The author also has a tendency to draw out chapters too long and repeat things too many times. Even so, I think this is a great resource for beginners and for anyone who could use some help to make their data visualizations more compelling.
This book has everything you need to do just that. Berinato breaks down the entire process, providing a step-by-step plan to create incredibly effective visualizations that will help you achieve your goals. He starts from the very basics, explaining what makes a good chart, what elements you should include, what to leave out, and how to present your data for maximum impact.
But Berinato doesn't leave you hanging there. Once the chart is complete, he shows you how to present it to your audience to achieve a positive outcome. But the most interesting section was the ethical one and whether you should manipulate the data in your favour.
Unfortunately, I read an advanced digital copy that had the graphics all messed up. Rather than enhance the content, it just confused me. If you're interested in this book, definitely pick up an old-school, physical copy.
The author also has a tendency to draw out chapters too long and repeat things too many times. Even so, I think this is a great resource for beginners and for anyone who could use some help to make their data visualizations more compelling.
March 21, 2017
My role as a software architect requires dealing with complex problems. At many times, I need to present my thoughts in the most effective manner to my fellow peers. I use a lot of charts both from a development and communication front. Before picking this book, I had wanted to enhance my skills in this particular area, to understand the science and psychology behind making effective visualizations. This book did not disappoint me a single bit. It is really surprising to see that this is the author's first book (at least according to GR), it looks like he has been writing books for ages - the structure, the presentation, the examples, the references were all top class. I'll recommend this book to anyone whose role touches on making presentations, especially data scientists.
August 1, 2019
This is a very good book on visualisations and charts. I'd recommend it to anyone. -1 star because it's offensively orange and teal.
February 28, 2022
Lots of good principles and guidelines to follow.
October 25, 2018
Good, organized and full of color book, with uniqe title. It describes how to take charts seriously avoiding short cut of using Excel charts without give the charts a deeper look.
July 10, 2021
Truly a Visual Persuasion Primer - While I began paging through this book when recently preparing for a presentation, I did not get to access or complete it at the time. My session went well enough, but now I will have some useful tips for next time and increased understanding on data visualization use. The book’s extended title truly does represent its contents--- a visual persuasion primer. I only wish I had had a book like this earlier during my consulting days as pervasive use of such visuals is clearly the stock and trade of the profession (see my review of McDonald’s "The Firm: The Story of McKinsey and Its Secret Influence on American Business") and it continues to extend into other fields (see my review of Huber and Morreale’s "Disciplinary Styles in the Scholarship of Teaching and Learning: Exploring Common Ground").
The book proceeds via an Introduction, Four Parts: (I) Understand, (II) Create, (III) Refine (IV) Present to Persuade ----with eight chapters----and a Conclusion. Basically, it goes through some history on data visualization and simple science on how it works. Text and many diagrams relate types of charts and a process for improving their creation: prep, talk and listen, sketch and prototype. It continues with steps to more-persuasive charts as well as ethical considerations to avoid manipulation. Finally, Berinato deals with how we can use charts to tell stories that move audiences and continually improve our data viz abilities.
Among the aspects that I liked were when the author associates data visualization and music as in where he says “I’ve compared of learning dataviz to learning how to write and to learning a new language. Maybe the best analog, though, is music. . . Unlike music, though, infoviz theory is new and changing. It draws on multiple disciplines, including perception science, neuroscience, and psychology.” Along these lines he indicates, “. . . just as composers use music theory to create music that produces certain predictable effects on an audience, chart makers can use visual perception theory to make more-effective visualizations.” The tips (e.g. the 2X2 data declarative/confirmation vs. exploration matrix) for determining the type of charting to use, the process, revising to make main ideas stand-out and convince were also significant for me. Finally, I found measures to make sure charts don’t deceive and using them to tell compelling stories to be most important (see my reviews of Frommer’s "How PowerPoint Makes You Stupid: The Faulty Causality, Sloppy Logic, Decontextualized Data, and Seductive Showmanship That Have Taken Over Our Thinking" and the Heaths’ "Made to Stick: Why Some Ideas Survive and Others Die").
As Berinato indicates, “We build a smart viz and hope that the chart itself—this clear, self-sufficient, persuasive little object of visual communication—will engage an audience. But the text of a brilliant speech doesn’t compel an audience to action; the orator does. . . The twin challenges here are to help people when they first see the visual—how you present it to them—and to help them process it: how you get them to engage with it.” He continues later to counsel that “In general, when we tell stories, the setup and resolution get about half of our attention. The other half is devoted to the conflict. That’s where the action is. That’s what makes narrative. No change, no story. . . First sketch out the three main parts of the drama, in words and literal sketches: You’ve mapped out a story. Now you have to build those charts.”
While the author deals with many different charts and mentions dataviz software, he does not go into emerging applications such as graph databases (see my review of Needham and Hodler’s "Graph Algorithms: Practical Examples in Apache Spark and Neo4j" which does address the differences between charts and graphs). It seems that Berinato’s presentation lessons will apply in a similar manner, but there may be some additional “wrinkles” when using these new forms of data and visualization that we will discover as we use them. Also in the Kindle edition the graphics in the book are not in color and as readily grasped as in the print edition I assume.
Regardless, if you are working with data visualization, get into this primer on persuasion to get the best use and results out of your efforts.
The book proceeds via an Introduction, Four Parts: (I) Understand, (II) Create, (III) Refine (IV) Present to Persuade ----with eight chapters----and a Conclusion. Basically, it goes through some history on data visualization and simple science on how it works. Text and many diagrams relate types of charts and a process for improving their creation: prep, talk and listen, sketch and prototype. It continues with steps to more-persuasive charts as well as ethical considerations to avoid manipulation. Finally, Berinato deals with how we can use charts to tell stories that move audiences and continually improve our data viz abilities.
Among the aspects that I liked were when the author associates data visualization and music as in where he says “I’ve compared of learning dataviz to learning how to write and to learning a new language. Maybe the best analog, though, is music. . . Unlike music, though, infoviz theory is new and changing. It draws on multiple disciplines, including perception science, neuroscience, and psychology.” Along these lines he indicates, “. . . just as composers use music theory to create music that produces certain predictable effects on an audience, chart makers can use visual perception theory to make more-effective visualizations.” The tips (e.g. the 2X2 data declarative/confirmation vs. exploration matrix) for determining the type of charting to use, the process, revising to make main ideas stand-out and convince were also significant for me. Finally, I found measures to make sure charts don’t deceive and using them to tell compelling stories to be most important (see my reviews of Frommer’s "How PowerPoint Makes You Stupid: The Faulty Causality, Sloppy Logic, Decontextualized Data, and Seductive Showmanship That Have Taken Over Our Thinking" and the Heaths’ "Made to Stick: Why Some Ideas Survive and Others Die").
As Berinato indicates, “We build a smart viz and hope that the chart itself—this clear, self-sufficient, persuasive little object of visual communication—will engage an audience. But the text of a brilliant speech doesn’t compel an audience to action; the orator does. . . The twin challenges here are to help people when they first see the visual—how you present it to them—and to help them process it: how you get them to engage with it.” He continues later to counsel that “In general, when we tell stories, the setup and resolution get about half of our attention. The other half is devoted to the conflict. That’s where the action is. That’s what makes narrative. No change, no story. . . First sketch out the three main parts of the drama, in words and literal sketches: You’ve mapped out a story. Now you have to build those charts.”
While the author deals with many different charts and mentions dataviz software, he does not go into emerging applications such as graph databases (see my review of Needham and Hodler’s "Graph Algorithms: Practical Examples in Apache Spark and Neo4j" which does address the differences between charts and graphs). It seems that Berinato’s presentation lessons will apply in a similar manner, but there may be some additional “wrinkles” when using these new forms of data and visualization that we will discover as we use them. Also in the Kindle edition the graphics in the book are not in color and as readily grasped as in the print edition I assume.
Regardless, if you are working with data visualization, get into this primer on persuasion to get the best use and results out of your efforts.
July 29, 2025
Clear frameworks, disciplined iteration and a firm “remove what doesn’t serve the story” ethic—Scott Berinato’s Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations is less a design treatise than a practical operating manual for business people who must turn numbers into decisions.
Berinato structures the book around a four-step cycle—Understand, Create, Refine, Present—showing why the real work begins long before a charting tool opens. The opening chapters press readers to articulate purpose: which question the data must answer and for whom. Without that anchor, later design choices, no matter how polished, risk being irrelevant.
His “Two Questions → Four Types” matrix is the book’s organising lens. By asking whether you are dealing with concepts or data, and whether the goal is exploration or declaration, you land in one of four quadrants—Idea Illustration, Everyday Dataviz, Visual Discovery or Idea Generation. This simple grid prevents common misfires such as using an exploratory dashboard to make a board-level recommendation or, conversely, over-simplifying analysis that ought to remain interactive.
The middle section translates perception research into practical editing. Five laws—our eyes jump to contrast, grasp only a few objects at once and immediately weave causal stories—become criteria for removing gridlines, re-ordering legends or isolating a key series. Berinato does not merely tell; he shows, walking through incremental revisions of real charts so the cumulative effect of small changes is unmistakable.
A separate chapter draws the ethical boundary between persuasion and manipulation. Examples of truncated axes, dual scales and misleading maps demonstrate how even well-intentioned design can distort. The discussion is balanced: emphasising context and transparency rather than advocating hard rules that would stifle clarity.
The final pages focus on delivery. Storyboarding, brief intentional pauses and a three-part “setup–conflict–resolution” structure help presenters guide an audience from first glance to actionable insight without overwhelming detail. A concise visual-crit routine—first impression, core message, priorities for change—offers a repeatable method for peer or self-review.
Berinato writes in a direct, conversational style that remains appropriate for a business readership. Occasional motivational asides surface, but they serve mainly to keep momentum rather than to dramatise the subject. Readers seeking deep statistical validation will find the evidence primarily illustrative, yet the pragmatic value is high: finish a chapter, and you can immediately apply its checklists to a live deck or dashboard.
Verdict: 4.5 / 5. A practical, well-structured guide that turns design principles into everyday business habits. Read it with a current presentation in hand; the payoff arrives as soon as you start cutting unnecessary ink and sharpening your headline.
Further training?
• Good Charts Workbook — red-pen homework straight from Berinato.
• Storytelling with Data by Cole Knaflic — a calmer, zen take on business slides.
• The Big Book of Dashboards by Wexler, Shaffer & Cotgreave — when your charts need to live in Tableau or Power BI.
Berinato structures the book around a four-step cycle—Understand, Create, Refine, Present—showing why the real work begins long before a charting tool opens. The opening chapters press readers to articulate purpose: which question the data must answer and for whom. Without that anchor, later design choices, no matter how polished, risk being irrelevant.
His “Two Questions → Four Types” matrix is the book’s organising lens. By asking whether you are dealing with concepts or data, and whether the goal is exploration or declaration, you land in one of four quadrants—Idea Illustration, Everyday Dataviz, Visual Discovery or Idea Generation. This simple grid prevents common misfires such as using an exploratory dashboard to make a board-level recommendation or, conversely, over-simplifying analysis that ought to remain interactive.
The middle section translates perception research into practical editing. Five laws—our eyes jump to contrast, grasp only a few objects at once and immediately weave causal stories—become criteria for removing gridlines, re-ordering legends or isolating a key series. Berinato does not merely tell; he shows, walking through incremental revisions of real charts so the cumulative effect of small changes is unmistakable.
A separate chapter draws the ethical boundary between persuasion and manipulation. Examples of truncated axes, dual scales and misleading maps demonstrate how even well-intentioned design can distort. The discussion is balanced: emphasising context and transparency rather than advocating hard rules that would stifle clarity.
The final pages focus on delivery. Storyboarding, brief intentional pauses and a three-part “setup–conflict–resolution” structure help presenters guide an audience from first glance to actionable insight without overwhelming detail. A concise visual-crit routine—first impression, core message, priorities for change—offers a repeatable method for peer or self-review.
Berinato writes in a direct, conversational style that remains appropriate for a business readership. Occasional motivational asides surface, but they serve mainly to keep momentum rather than to dramatise the subject. Readers seeking deep statistical validation will find the evidence primarily illustrative, yet the pragmatic value is high: finish a chapter, and you can immediately apply its checklists to a live deck or dashboard.
Verdict: 4.5 / 5. A practical, well-structured guide that turns design principles into everyday business habits. Read it with a current presentation in hand; the payoff arrives as soon as you start cutting unnecessary ink and sharpening your headline.
Further training?
• Good Charts Workbook — red-pen homework straight from Berinato.
• Storytelling with Data by Cole Knaflic — a calmer, zen take on business slides.
• The Big Book of Dashboards by Wexler, Shaffer & Cotgreave — when your charts need to live in Tableau or Power BI.
July 10, 2018
TODO full review:
+ Overall, a book on information visualization. The book excels at explaining the craft of making and presenting high-quality graphs to the reader. Somewhere stricter and deeper than Stephen Few and Dana M. Wong, and more lenient and lighter than Edward R. Tufte.
+/- Short intro to the history of information visualization. Much better (and equally short) intro to the science of visual perception. Colin Ware (not mentioned), William S. Cleveland, and Edward R. Tufte? Too old-school, and the new science, Ronald Rensink and Lane Harrison mentioned, give new directions in information visualization (and cognitive sciences). Then, a practical chapter on how our eyes react to visual information, of good quality.
++/- The structured chapter on creating graphs, with much hand-holding but good graphs.
+++ Excellent chapter on quick design sessions, in the sequence preparation, discussion with a stakeholder or friend, sketching, and prototyping. Learned also about Andrew Abela's chart types, and about the extension proposed by Scott Berinato; cool stuff. The list of proposed software for each stage in the process (but ... these stages are not exactly the four the chapter focuses on!?) is modern and ... yet already somewhat outdates... data scientists increasingly use Spark and Spark-based tools, not Tableau. But D3 and plot.ly, plus Google stuff are all included.
++/-- Chapter 5, on refinement, is concise but good. With Chapter 6, on making graphs more persuasive, they would make very good, but ... is this ethical? Chapter 7 tries to be clear, but ends up being murky. Also, why split into so many chapters this part?
+++ The chapter on presenting graphs is excellent. Not only I learned something, but I also saw myself discussing this part with my team.
+++ The chapter on improving someone else's graphs is also very nice. It matches the chapter on refinement but goes in much more depth. There is a proposed improvement of a graph from the Economist I even remember... don't recall exactly with what. But good process.
+ A summary of types of graphs, with pros and cons briefly summarized.
+ Overall, a book on information visualization. The book excels at explaining the craft of making and presenting high-quality graphs to the reader. Somewhere stricter and deeper than Stephen Few and Dana M. Wong, and more lenient and lighter than Edward R. Tufte.
+/- Short intro to the history of information visualization. Much better (and equally short) intro to the science of visual perception. Colin Ware (not mentioned), William S. Cleveland, and Edward R. Tufte? Too old-school, and the new science, Ronald Rensink and Lane Harrison mentioned, give new directions in information visualization (and cognitive sciences). Then, a practical chapter on how our eyes react to visual information, of good quality.
++/- The structured chapter on creating graphs, with much hand-holding but good graphs.
+++ Excellent chapter on quick design sessions, in the sequence preparation, discussion with a stakeholder or friend, sketching, and prototyping. Learned also about Andrew Abela's chart types, and about the extension proposed by Scott Berinato; cool stuff. The list of proposed software for each stage in the process (but ... these stages are not exactly the four the chapter focuses on!?) is modern and ... yet already somewhat outdates... data scientists increasingly use Spark and Spark-based tools, not Tableau. But D3 and plot.ly, plus Google stuff are all included.
++/-- Chapter 5, on refinement, is concise but good. With Chapter 6, on making graphs more persuasive, they would make very good, but ... is this ethical? Chapter 7 tries to be clear, but ends up being murky. Also, why split into so many chapters this part?
+++ The chapter on presenting graphs is excellent. Not only I learned something, but I also saw myself discussing this part with my team.
+++ The chapter on improving someone else's graphs is also very nice. It matches the chapter on refinement but goes in much more depth. There is a proposed improvement of a graph from the Economist I even remember... don't recall exactly with what. But good process.
+ A summary of types of graphs, with pros and cons briefly summarized.
August 19, 2024
"Good Charts" di Scott Berinato si distingue come una risorsa fondamentale per chiunque desideri perfezionare le proprie competenze nella visualizzazione dei dati. Questo libro non solo brilla per la qualità delle immagini e dei grafici presentati, ma offre anche una guida pratica e ben strutturata che si rivolge tanto ai principianti quanto ai professionisti esperti. La scrittura è chiara e coinvolgente, facilitando l'apprendimento e la comprensione dei concetti trattati.
Vantaggi principali:
Contenuti di alta qualità: Il libro è una guida completa che introduce i principi fondamentali della visualizzazione dei dati, rendendolo un ottimo punto di partenza per chiunque desideri migliorare le proprie competenze in questo campo.
Eccellenti esempi visivi: Con una vasta gamma di grafici e immagini, il libro non solo illustra i concetti teorici ma mostra anche esempi concreti di come applicarli, ispirando il lettore a creare visualizzazioni efficaci.
Guida pratica: Ogni capitolo si conclude con riassunti e passaggi pratici che aiutano a mettere in pratica immediatamente quanto appreso.
Applicabilità immediata: I suggerimenti offerti sono prontamente applicabili a chi lavora con grafici e presentazioni, rendendo il libro un utile strumento di lavoro.
Scrittura accessibile: Il linguaggio utilizzato è diretto e coinvolgente, facilitando la lettura anche per chi non ha una formazione specialistica.
Svantaggi:
Ripetitività: Alcuni argomenti vengono ripetuti più volte, il che può rendere la lettura un po' ridondante.
Esperienza digitale deludente: La qualità delle visualizzazioni grafiche può risultare compromessa nella versione e-book, rendendo difficile seguire alcuni esempi sullo schermo.
In sintesi, "Good Charts" è una lettura indispensabile per chiunque desideri affinare le proprie competenze nella visualizzazione dei dati, offrendo sia ispirazione che strumenti pratici per creare grafici più efficaci e significativi.
Vantaggi principali:
Contenuti di alta qualità: Il libro è una guida completa che introduce i principi fondamentali della visualizzazione dei dati, rendendolo un ottimo punto di partenza per chiunque desideri migliorare le proprie competenze in questo campo.
Eccellenti esempi visivi: Con una vasta gamma di grafici e immagini, il libro non solo illustra i concetti teorici ma mostra anche esempi concreti di come applicarli, ispirando il lettore a creare visualizzazioni efficaci.
Guida pratica: Ogni capitolo si conclude con riassunti e passaggi pratici che aiutano a mettere in pratica immediatamente quanto appreso.
Applicabilità immediata: I suggerimenti offerti sono prontamente applicabili a chi lavora con grafici e presentazioni, rendendo il libro un utile strumento di lavoro.
Scrittura accessibile: Il linguaggio utilizzato è diretto e coinvolgente, facilitando la lettura anche per chi non ha una formazione specialistica.
Svantaggi:
Ripetitività: Alcuni argomenti vengono ripetuti più volte, il che può rendere la lettura un po' ridondante.
Esperienza digitale deludente: La qualità delle visualizzazioni grafiche può risultare compromessa nella versione e-book, rendendo difficile seguire alcuni esempi sullo schermo.
In sintesi, "Good Charts" è una lettura indispensabile per chiunque desideri affinare le proprie competenze nella visualizzazione dei dati, offrendo sia ispirazione che strumenti pratici per creare grafici più efficaci e significativi.
September 27, 2022
After starting out in a new position, I started to expand my reading list to something like this. To my surprise, this is such a good book. I am a data nerd, currently studying a course to become a Data Analytics Professional. After some experience in a fast paced work environment, I've realized: a good chart is crucial. Letting the reader know every message you wanted to depict just by one chart and a few legends is legendary /pun intended/.
What I really liked about this the psychology of a human mind. This book tells you at which points, which color combinations a human mind finds most pleasing, and useful.
One chapter in this book is called Persuasion or Manipulation? This chapter is particularly fascinating cause I've had many instances where I thought a chart or a figure was trying to manipulate me to a certain conclusion. So this fine line of what is the right amount of persuasion and at which level it becomes manipulation is certainly interesting.
Me, a visual and kinesthetic learner, found this book to be very much useful. There is also a workbook to this book, which satisfies my kinesthetic learning needs as well. Perfect!
What I really liked about this the psychology of a human mind. This book tells you at which points, which color combinations a human mind finds most pleasing, and useful.
One chapter in this book is called Persuasion or Manipulation? This chapter is particularly fascinating cause I've had many instances where I thought a chart or a figure was trying to manipulate me to a certain conclusion. So this fine line of what is the right amount of persuasion and at which level it becomes manipulation is certainly interesting.
Me, a visual and kinesthetic learner, found this book to be very much useful. There is also a workbook to this book, which satisfies my kinesthetic learning needs as well. Perfect!
July 5, 2017
A really excellent book for anyone who needs to make charts and graphs on a regular basis. Even if "dataviz" isn't really what you do, this has amazing advice on how charts work and how to communicate and present effectively.
The writing is less formal than you might expect for this subject. It's very engaging and down-to-earth. And each chapter ends with a summary that steps you through the actions they've taught you about - this makes the book an invaluable reference. It's going to live in my laptop case so I always have it nearby when I need a reminder to talk and sketch first, or to assess what can be removed from a chart to improve it.
I enjoyed this so much and found it so valuable, I'm now looking for a similar book on PowerPoint presentations - something you see used poorly all the time, but for which really great skill can seem elusive.
The writing is less formal than you might expect for this subject. It's very engaging and down-to-earth. And each chapter ends with a summary that steps you through the actions they've taught you about - this makes the book an invaluable reference. It's going to live in my laptop case so I always have it nearby when I need a reminder to talk and sketch first, or to assess what can be removed from a chart to improve it.
I enjoyed this so much and found it so valuable, I'm now looking for a similar book on PowerPoint presentations - something you see used poorly all the time, but for which really great skill can seem elusive.
January 16, 2023
The Good Charts provides a framework for an effective visual presentation. For example, always ask yourself these two questions for your coming presentations: is the information to be presented conceptual or data-driven and are your visuals meant to be declarative or exploratory.
As titled, the book heavily uses charts to explain concepts, examples, and make the key points. It's an easy read. Although this book gives various examples of charts, the secret to building a good chart should be starting from what you want to show rather than from what data you have on hand.
Although it's not a weakness of this book, as the book meant to teach you how to effectively use charts rather than the what. I personally prefer to see a section to show pros & cons of different types of charts with real world examples to demonstrate the difference.
As titled, the book heavily uses charts to explain concepts, examples, and make the key points. It's an easy read. Although this book gives various examples of charts, the secret to building a good chart should be starting from what you want to show rather than from what data you have on hand.
Although it's not a weakness of this book, as the book meant to teach you how to effectively use charts rather than the what. I personally prefer to see a section to show pros & cons of different types of charts with real world examples to demonstrate the difference.
August 28, 2022
Very informative introduction to chart design. The author does an effective job laying out the various considerations that should be understood before mapping data (or translating a concept) to a graph. I liked the clear framework he provides to classify the purpose of the graph, and then how one should consider the best to use visuals to convey that message. I found after reading this book that I became more critical of poor or mediocre graphs that, even if attractive, can miss the mark in conveying a clear message. I recommend this book if you're looking for some practical tips and a strategy for becoming more effective at graphing.
October 5, 2017
This is a great book for people who consume and/or produce dataviz.
First off, it's just a beautiful book to look through. Everything is high quality. The book is well-structured too, with a clear table of contents and chapter summaries. Those always make me happy.
Mr. Berinato covers everything from what makes a good chart, how to create a good chart, through how to present a good chart. I hadn't spent as much time thinking about how to present a good chart, so that section in particular was helpful for me. I had several takeaways from that.
First off, it's just a beautiful book to look through. Everything is high quality. The book is well-structured too, with a clear table of contents and chapter summaries. Those always make me happy.
Mr. Berinato covers everything from what makes a good chart, how to create a good chart, through how to present a good chart. I hadn't spent as much time thinking about how to present a good chart, so that section in particular was helpful for me. I had several takeaways from that.
November 16, 2018
Enjoyed this book - it's a great overall read for someone who wants to get better at, well, making good charts. I particularly love the part on the "design process" for chart creation - sketching, prototyping, iteration.
I was hoping for a little more academic detail at the beginning to explain some principles of great chart design, and to perhaps touch on the Tufte-McCandless spectrum. I often find books on data visualization to be a little light academic rigour. But perhaps I was not quite the intended audience.
I was hoping for a little more academic detail at the beginning to explain some principles of great chart design, and to perhaps touch on the Tufte-McCandless spectrum. I often find books on data visualization to be a little light academic rigour. But perhaps I was not quite the intended audience.
October 14, 2020
My reading experience would have been seriously improved by reading a physical book and not an e-book. Unsurprisingly, this book leverages data visualizations quite frequently which are almost incomprehensible on a kindle. It does make following the flow of the book difficult.
I thought Berinato provided good tips to reimagine how we think about data viz. Definitely some tips rise to the level of once you see it, you can't unsee it. However, like many nonfiction books, it gets a little repetitive to get the point across.
I thought Berinato provided good tips to reimagine how we think about data viz. Definitely some tips rise to the level of once you see it, you can't unsee it. However, like many nonfiction books, it gets a little repetitive to get the point across.
January 1, 2021
Quick recap.
Most charts just show the data without story. By asking "what do I want to convince people about", I can do better graphs. Emphasize, isolate, make the idea stand out. Use titles and subtitles, dont wear belts and suspenders, never have duplicity in the graphs. Tell a story. Dissect ideas, tell them after each other, use timing. When presenting, use timing again. Let people think about the visualization.
Most charts just show the data without story. By asking "what do I want to convince people about", I can do better graphs. Emphasize, isolate, make the idea stand out. Use titles and subtitles, dont wear belts and suspenders, never have duplicity in the graphs. Tell a story. Dissect ideas, tell them after each other, use timing. When presenting, use timing again. Let people think about the visualization.
February 15, 2025
ภาพเราสนสิ่งที่เด่นสะดุดตาก่อน แล้วเราก็มองแค่ไม่กี่อย่าง
เราชอบเชื่อมโยงความสัมพันธ์ตามที่เรามโน
และเราก็ชอบเปรียบเทียบเสมอ
ภาพเน้นแสดงอะไร
อธิบาย, ระดมสมอง, ค้นหา, งานทั่วไป
ขั้นตอนทำ
1.เตรียมตัว
2.คุย
3.ร่างภาพ
4.สร้างต้นแบบ
ขัดเกลาให้ภาพสะอาดตา เน้นโครงสร้างจัดลำดับ
ดูรู้เรื่อง เน้นชัดเจน
ดูสวย เน้นเรียบง่าย
จูงใจด้วยภาพเน้น ตัดสิ่งไม่จำเป็นทิ้ง เพิ่มเติมจุดเด่น เปลี่ยนใหม่เพื่อเสนอแนวคิดใหม่
ภาพหลอก ด้วย หั่นแกนตั้งทิ้งสเกลหลอกตา มี2แกนข้อมูลคนละอย่างทำคิดว่าเกี่ยวกัน แผนที่ทำให้เข้าใจสัดส่วนผิด
นำเสนอภาพด้วย ปล่อยให้มองเงียบๆ พูดไร้คำบรรยาย คำบรรยายภาพพิเศษตัวเปรียบเทียบ จะพูดให้ปิดภาพ ภาพเรียบง่ายนำเสนอ ภาพซับซ้อนศึกษา
มีส่วนร่วมด้วย สร้างความกดดัน ค่อยโผล่ ไล่ขนาด ค่อยๆให้คนคาดหวัง ริ้อภาพประกอบใหม่ เล่าเรื่องราว
วิจารณ์ภาพ บันทึกสิ่งที่เห็น จดสิ่งที่คิดออก จดว่าชอบไม่ชอบอยากเห็นอะไร 3สิ่งที่อยากปรับ ร่างภาพ
เราชอบเชื่อมโยงความสัมพันธ์ตามที่เรามโน
และเราก็ชอบเปรียบเทียบเสมอ
ภาพเน้นแสดงอะไร
อธิบาย, ระดมสมอง, ค้นหา, งานทั่วไป
ขั้นตอนทำ
1.เตรียมตัว
2.คุย
3.ร่างภาพ
4.สร้างต้นแบบ
ขัดเกลาให้ภาพสะอาดตา เน้นโครงสร้างจัดลำดับ
ดูรู้เรื่อง เน้นชัดเจน
ดูสวย เน้นเรียบง่าย
จูงใจด้วยภาพเน้น ตัดสิ่งไม่จำเป็นทิ้ง เพิ่มเติมจุดเด่น เปลี่ยนใหม่เพื่อเสนอแนวคิดใหม่
ภาพหลอก ด้วย หั่นแกนตั้งทิ้งสเกลหลอกตา มี2แกนข้อมูลคนละอย่างทำคิดว่าเกี่ยวกัน แผนที่ทำให้เข้าใจสัดส่วนผิด
นำเสนอภาพด้วย ปล่อยให้มองเงียบๆ พูดไร้คำบรรยาย คำบรรยายภาพพิเศษตัวเปรียบเทียบ จะพูดให้ปิดภาพ ภาพเรียบง่ายนำเสนอ ภาพซับซ้อนศึกษา
มีส่วนร่วมด้วย สร้างความกดดัน ค่อยโผล่ ไล่ขนาด ค่อยๆให้คนคาดหวัง ริ้อภาพประกอบใหม่ เล่าเรื่องราว
วิจารณ์ภาพ บันทึกสิ่งที่เห็น จดสิ่งที่คิดออก จดว่าชอบไม่ชอบอยากเห็นอะไร 3สิ่งที่อยากปรับ ร่างภาพ
September 13, 2018
This book is full of interesting techniques and examples to help get your point across. It emphasizes simplifying the visual representation by using gray to de-emphasize some data, reducing the number of mundane datapoints, and controlling how the data is grouped. It also provides a useful guide for charts depending on how exploratory you want the conversation to be.
December 3, 2018
This is a great book. If you want to delve into the world of data visualization, this book is definitely your entry gateway.
The author sets a framework of designing charts and Data visualization using a mix of science and art.
I recommend this book for information management, business intelligence, and Data visualization consultants.
The author sets a framework of designing charts and Data visualization using a mix of science and art.
I recommend this book for information management, business intelligence, and Data visualization consultants.
January 16, 2019
Good visualizations are important and in this book Scott Berinato shared insights on data visualization and described how to turn uninspiring charts into smart, effective visualizations that powerfully convey ideas.
I really enjoyed reading this book. I got many insights which I can implement in my work.
I really enjoyed reading this book. I got many insights which I can implement in my work.
January 20, 2020
Awesome book! I work in management and among other things I am responsible for the data visualisation, charts, reports. Often we hear many wishes for some fresh and exciting reports, and this book has shown me what’s possible & how to steer the conversation in the right direction. I loved as well all the practical tips from the corporate world, examples, ... so yes, five stars!
September 7, 2020
An accessible and surprisingly comprehensive introduction to data visualisation geared towards non-data people. It's written in such a way that beginners and non-beginners alike will likely take away lots of useful ideas, although I suspect more advanced dataviz professionals might not find it helpful.
I took a ton of notes (and some photos, too!)
I took a ton of notes (and some photos, too!)
October 25, 2020
The book guides readers through the process of designing data visualizations. Easier to apply and more up-to-date than Tufte's books. It includes a huge number of examples of good and bad graphs. The accompanying text is written in the form of somewhat disjointed blurbs that are sometimes too short or too unclear to be useful. 3.75 stars.
March 10, 2021
A direct and accessible text that celebrates the art of data visualization while explaining its finer points. Even if you do not use a Business Intelligence software package this book will help you increase your efficacy in designing slides, tables, and charts. Further, Scott does all this without an ounce of judgement for those of us non-artists.
July 28, 2017
An amazingly powerful, accessible work on data visualization and the many skills we need to practice to do it well. This is a must read book for anyone who wants to find and communicate key insights from data sets.
December 20, 2017
If you read only one book on dataviz, let it be this one
I’ve read several books on data visualization, but this is a great summary of the literature out there. If you don’t have time to delve into dataviz and design, read this one—it’ll get you 80% there.
I’ve read several books on data visualization, but this is a great summary of the literature out there. If you don’t have time to delve into dataviz and design, read this one—it’ll get you 80% there.
December 27, 2017
Amazing book on where to start, improve and produce the best graphs.
Not very technical in terms of "how-to", but it will give you the best guidance towards on how to systematize a graphical report.
I use a lot of what I learned from this book in order to produce the best dashboards.
Not very technical in terms of "how-to", but it will give you the best guidance towards on how to systematize a graphical report.
I use a lot of what I learned from this book in order to produce the best dashboards.
June 28, 2020
The book is ideal for the ones who seek to improve their visual communication. Not only does it present helpful insights on creating beautiful and clean charts but also walk you through the path of conceiving good presentation.
Displaying 1 - 30 of 78 reviews