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Storytelling with Data: A Data Visualization Guide for Business Professionals
Ebook Free Storytelling with Data: A Data Visualization Guide for Business Professionals
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Audible Audiobook
Listening Length: 5 hours and 43 minutes
Program Type: Audiobook
Version: Unabridged
Publisher: Audible Studios
Audible.com Release Date: January 31, 2018
Language: English, English
ASIN: B079H3ZJJZ
Amazon Best Sellers Rank:
I am a university professor who teaches biostatistics and I find this to be one of the best books that bridges the gap between analytics and presentation. There are some excellent books around that show visualization (e.g., The Wall Street Journal Guide to Information Graphics: The Dos and Don'ts of Presenting Data, Facts, and Figures or books by Few Information Dashboard Design: Displaying Data for At-a-Glance Monitoring &Show Me the Numbers: Designing Tables and Graphs to Enlighten or Cairo The Truthful Art: Data, Charts, and Maps for Communication) and there are good books on presentation (in particular I love Duarte's books Resonate: Present Visual Stories that Transform Audiences) but this book is unique in how well it blends the two topics. I have never seen such an excellent presentation on how to build a series of graphics. That is, with books by Few or Cairo you will know how to make *a* great graphic and with advice from Duarte, you can connect with your audience but with this book you will see how to build a series of interrelated graphics that highlight different parts of a dataset. Most of the examples are spun around business but the examples are easy to extend to any field.While I think the author wrote this for people who do presentations in any quantitative field for a living, this book should be required reading for graduate students preparing to defend a dissertation or thesis.
People wanting a basic introduction to presentation graphics would bewell served by this book by Cole Nussbaumer Knaflic. Prerequisites areminimal: there is almost no mathematical content and no use of any butthe most elementary statistical methods. Knaflic's encouraging messageis that MS Excel and PowerPoint can be quite enough software for goodgraphics, but you will need to go beyond the defaults and work at thedetails.Almost all the examples are of very small datasets already to hand withtwo-way structure. 2 variables for 12 months and 5 products for 7 yearsare typical sizes. In practice when analysing data it can be hard workdeciding what methods to use and reducing a mass of raw data to aconcise summary. These steps, sometimes most of a project, are hereassumed already done.The subtitle flags a focus on "business professionals"; the contenttactfully implies junior people presenting with PowerPoint totime-challenged bosses at brief meetings. Seemingly few write reports tobe read any more, or use any other presentation software.Knaflic is excellent on the need to keep things simple. She has a goodeye and sound logic on what looks and works well and what does not.Examples show how mediocre graphs can be improved by reducing clutter,killing the key, better use of color, and similar standard tricks.Horizontal bar charts are usually more readable than vertical, and piecharts and a false third dimension are best avoided: these points havebeen well made many times, yet do deserve forceful repetition. Variouskinds of bar and line charts are her main work-horses.Sometimes the discussion seems a little contrived, as poor graphs areset up to be shot down, but that's often what convinces. Readers shouldbe on the author's side as she encourages us towards effective andtasteful graphics. Her combinations of blue for data deserving emphasisand grey for data providing context -- or of blue and orange for groupsto contrast -- are good design patterns for experienced analysts as wellas outright beginners.The closing chapters are more long-winded and repetitive, but do includesmall gems. A splendid case study on avoiding spaghetti graphics (lotsof tangled lines) stands out, and the problem and the ideas deservedmore.I always find it disappointing when datasets are fabricated orsufficiently anonymous that they might as well be. People care mostabout their own data which an author cannot provide, and confidentialityconstraints often bite, but real data examples are still generallypreferable to fake. Too many examples here are variants on Products A toE or Features A to O. Unfortunately an outrageous example of a barchart from a well-known U.S. television news network (p.50) seems alltoo real.What's not here includes Cleveland dot charts, histograms and box plotseven among the staples of good introductory statistics courses, letalone (say) use of logarithmic scale, always one of the first graphicaldevices for many sciences. So if you want something with morestatistical bite or depth, you need to look elsewhere. Naomi Robbins'excellent, no nonsense Creating more effective graphshttp://www.amazon.com/Creating-Effective-Graphs-Naomi-Robbins/dp/0985911123would enable you to go further.As in any first edition there are some small slips and exaggeratedclaims. 40% is not a majority (p.5). There is confusion between numberand percentage on p.39. Any rule that "bar charts must have a zerobaseline" (p.52) is simplistic. It is quite correct that bar chartsshould encode departures from some sensible reference level. (Thetelevision network responsible should have paid attention.) But thatreference level could easily be some value not zero, such as paritybetween men and women, or the mean of a variable, or 32 degreesFahrenheit to separate freezing and non-freezing temperatures. Idisagree that every dollar amount or percent should be labeled as such(p.90); that is repetitive clutter such as Knaflic rightly deplores. Noris it an absolute principle that every axis needs a title. If the axislabels are 2008 to 2015, no one should need "Year" to explain what ishappening. Far from being "extremely rare" (p.141), several exceptionsto that principle are included in this book!A note on style: Inside a very useful book is an even more usefulshorter book struggling to get out. For my taste, the motivationalwarm-ups and little anecdotes are often too spun-out or too trite. Goodgraphics should be presented as illustrations within a good story: a keypoint, but not one that required a long chapter with digressions on RedRiding Hood or on Aristotle on drama, or advice from a junior highschool teacher. A tighter copy-editor would have signalled that"leverage" (used as a verb about 70 times) was too much of a personalfavorite, while "de-emphasize" for "tone down", "utilize" for "use" and"incredible" for things all too credible are among several otherrepeated tics.An easy solution is to skip and skim: if a book is on graphics, you canalways just look at the graphics. In this case, Knaflic has written aworthwhile book that, small details aside, does well what it tries todo.
This book was required by my data visualization class. I wasn't able to find a cheap used version of this book so I ended up reading the temporary PDF my school had at the library. Let's just say this... This book is SO good and SO useful, that I ended up shelling out money to buy it AFTER I've read the book already and AFTER the class was over. I think it's just such a handy guide for anyone to have. I'm sick of crappy presentations overloaded with meaningless data that don't convey any useful information. If you are too, I highly recommend this book.
This is far and away the BEST data vis book because it goes beyond the techniques for making visualizations to the ways in which you can connect with clients, co-researchers, and stakeholders. This is an essential book for effective reporting and dissemination of information. Truly exceptional.
Very rarely do I find a business book that so fully meets my needs and expectations...and then surpasses them.As a full-time business analyst who was hoping for some practical guidance to improve his visualisations, I was delighted by how clearly the author delivered it with her easily understood concepts and step-by-step demonstrations.Whether you are already acquainted with data analytics tools like Tableau but think your presentations look boring or you're an artistic designer who can't figure out how to use software to express your point, you need this book!
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