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#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time
Explore different perspectives and approaches to create more effective visualizations
#MakeoverMonday offers inspiration and a giant dose of perspective for those who communicate data. Originally a small project in the data visualization community, #MakeoverMonday features a weekly chart or graph and a dataset that community members reimagine in order to make it more effective. The results have been astounding; hundreds of people have contributed thousands of makeovers, perfectly illustrating the highly variable nature of data visualization. Different takes on the same data showed a wide variation of theme, focus, content, and design, with side-by-side comparisons throwing more- and less-effective techniques into sharp relief.
This book is an extension of that project, featuring a variety of makeovers that showcase various approaches to data communication and a focus on the analytical, design and storytelling skills that have been developed through #MakeoverMonday. Paging through the makeovers ignites immediate inspiration for your own work, provides insight into different perspectives, and highlights the techniques that truly make an impact.
Explore the many approaches to visual data communication Think beyond the data and consider audience, stakeholders, and message Design your graphs to be intuitive and more communicative Assess the impact of layout, color, font, chart type, and other design choices Creating visual representation of complex datasets is tricky. There's the mandate to include all relevant data in a clean, readable format that best illustrates what the data is saying--but there is also the designer's impetus to showcase a command of the complexity and create multidimensional visualizations that "look cool." #MakeoverMonday shows you the many ways to walk the line between simple reporting and design artistry to create exactly the visualization the situation requires.
#MakeoverMonday offers inspiration and a giant dose of perspective for those who communicate data. Originally a small project in the data visualization community, #MakeoverMonday features a weekly chart or graph and a dataset that community members reimagine in order to make it more effective. The results have been astounding; hundreds of people have contributed thousands of makeovers, perfectly illustrating the highly variable nature of data visualization. Different takes on the same data showed a wide variation of theme, focus, content, and design, with side-by-side comparisons throwing more- and less-effective techniques into sharp relief.
This book is an extension of that project, featuring a variety of makeovers that showcase various approaches to data communication and a focus on the analytical, design and storytelling skills that have been developed through #MakeoverMonday. Paging through the makeovers ignites immediate inspiration for your own work, provides insight into different perspectives, and highlights the techniques that truly make an impact.
Explore the many approaches to visual data communication Think beyond the data and consider audience, stakeholders, and message Design your graphs to be intuitive and more communicative Assess the impact of layout, color, font, chart type, and other design choices Creating visual representation of complex datasets is tricky. There's the mandate to include all relevant data in a clean, readable format that best illustrates what the data is saying--but there is also the designer's impetus to showcase a command of the complexity and create multidimensional visualizations that "look cool." #MakeoverMonday shows you the many ways to walk the line between simple reporting and design artistry to create exactly the visualization the situation requires.
496 pages, Kindle Edition
Published October 2, 2018
79 people are currently reading
264 people want to read
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Displaying 1 - 9 of 9 reviews
June 26, 2021
This is a good book for anyone interested in visualisation, for work or for play. The topics are wide-ranging, and was similar to what I've read in Stephen Fry's books (which is actually great), but also including things like stakeholder communication and the development process.
I think the one flaw for me was that you're not going to get focused insight or tips for any specific domain - for example if you create Sales dashboards (as I do) you may be looking for ways to show pipeline metrics and what best practices across industries are. Sorry, you're not going to find that here. What you will find though are many tips and insights that ARE applicable to creating sales dashboards in general.
So you may find another Sales dashboard book that tells you what graphs are best suited for deal size over time, and then you apply the general visualisation tips found here (colours; text; labelling; tooltips etc.)
Overall I think this is a great book especially for those who haven't read anything else on visualisation, or are pretty new to analytics.
I think the one flaw for me was that you're not going to get focused insight or tips for any specific domain - for example if you create Sales dashboards (as I do) you may be looking for ways to show pipeline metrics and what best practices across industries are. Sorry, you're not going to find that here. What you will find though are many tips and insights that ARE applicable to creating sales dashboards in general.
So you may find another Sales dashboard book that tells you what graphs are best suited for deal size over time, and then you apply the general visualisation tips found here (colours; text; labelling; tooltips etc.)
Overall I think this is a great book especially for those who haven't read anything else on visualisation, or are pretty new to analytics.
February 4, 2020
This book was a great introduction to data visualisation principles in the first half; unfortunately, because I already knew a lot of what it had to say, it dragged a little. The second half interested me more (and was more like what I was hoping the book would be), showing before and after of charts and the improvements the changes supplied (and text explaining why the changes helped).
I will probably buy a copy of the book to leave at the office for my co-workers to read, I think it is a good one to start with, but yeah, the first half of the book was a little basic for my knowledge level.
I will probably buy a copy of the book to leave at the office for my co-workers to read, I think it is a good one to start with, but yeah, the first half of the book was a little basic for my knowledge level.
January 2, 2019
Good read to further cement your knowledge, provide some examples and alternatives, or, if you’re just starting your journey, introduce ideas that will be crucial to your success.
The book catalogues the growth of the community over the years after it began as a personal project for Andy. Through each chapter new topics are brought in and allow quick reference as a book on your office desk or, as I’d recommend, read through it once in its entirety to gain some insight and then keep as a reference.
The book catalogues the growth of the community over the years after it began as a personal project for Andy. Through each chapter new topics are brought in and allow quick reference as a book on your office desk or, as I’d recommend, read through it once in its entirety to gain some insight and then keep as a reference.
December 31, 2023
It's an excellent book about data visualisation. I get a lot of inspiration and guidelines reading it - what works and what does not.
However, I give it 4 stars because it covers mainly data visualisation of one-time use data sets, e.g. there is not much content for daily / weekly / monthly reporting of financial data (or other business operational data), the data you use in business day-to-day operational dashboards.
However, I give it 4 stars because it covers mainly data visualisation of one-time use data sets, e.g. there is not much content for daily / weekly / monthly reporting of financial data (or other business operational data), the data you use in business day-to-day operational dashboards.
August 26, 2024
This book expands on the Makeover Monday movement by Andy Kriebel.
Most of this designing ideas are done in Tableau, but the ideas and practices can be done in any BI tool.
Topics such color, context, choosing the right chart, storytelling, cleaning data, organization, and sketching are covered, and plenty of good practices and to-avoid practices.
I consider it goes into the right amount of detail and can later serve as a reference
Most of this designing ideas are done in Tableau, but the ideas and practices can be done in any BI tool.
Topics such color, context, choosing the right chart, storytelling, cleaning data, organization, and sketching are covered, and plenty of good practices and to-avoid practices.
I consider it goes into the right amount of detail and can later serve as a reference
January 15, 2020
WOW - This book is incredible for anyone looking to improve their data analysis and visualization skills. It's full of practical information and you will truly learn so much. I recommend this so highly.
March 22, 2023
Excellent read for data visualization enthusiasts, wonderfully explained each and every aspects of visualization. The examples are awesome, it's kind of reference book for Data Science / Visualization.
July 1, 2021
Anyone that works with data should read!
Makeover Monday describes the aesthetics behind data and the Dos / Donts of displaying.
Makeover Monday describes the aesthetics behind data and the Dos / Donts of displaying.
June 2, 2019
A really compelling, tactical guide to data visualization! It left me feeling empowered to try some new strategies.
Displaying 1 - 9 of 9 reviews