File Size: 7316 KB
Print Length: 255 pages
Publisher: Wiley; 1 edition (October 7, 2015)
Publication Date: October 7, 2015
well served at this time book by Cole Nussbaumer Knaflic. Prerequisites are
little: there is very little statistical content and no use of any but
the most primary statistical methods. Knaflic's encouraging message
is that MS Excel and PowerPoint could be very enough software for good
graphics, but you will have to go beyond the defaults and work at the
Practically all the examples are of very small datasets already to hand with
two-way construction. 2 variables for twelve months and 5 products for six years
are typical sizes. In practice when analysing data it can be hard work
deciding what methods to use and reducing quite a few raw data to a
concise summary. These steps, sometimes the majority of task management, are here
thought already done.
The caption flags a concentrate on " business professionals"; the content
tactfully implies younger people presenting with PowerPoint to
time-challenged bosses at brief conferences. Seemingly few write reports to
be read any more, or use any other demonstration software.
Knaflic is excellent on the need to keep things simple. She gets a good
eye and sound logic on what looks and works well and what does not.
Examples show how mediocre graphs can be improved by reducing mess,
killing the key, better use of color, and similar standard tricks.
Side to side bar charts are usually more readable than straight, and pie
charts and a false 3rd dimension are best prevented: these points have
been well made many times, yet do deserve forceful repetition. Various
kinds of club and line charts are her main work-horses.
Occasionally the discussion seems a little contrived, as poor graphs are
established up to be chance down, but that's often what convinces. Readers should
land on the author's side as she encourages us towards effective and
stylish graphics. Her combinations of blue for data worthy emphasis
and grey for data providing context -- or of blue and orange for groups
to contrast -- are good design patterns for experienced analysts as well
as outright starters.
The closing chapters are more long-winded and recurring, but do include
small gems. A splendid case study on avoiding spaghetti graphics (lots
of tangled lines) stands out, and the problem and the ideas deserved
I always find it unsatisfactory when datasets are created or
adequately anonymous that they might as well be. Folks care most
about their own data which a writer cannot provide, and confidentiality
constraints often bite, but real data examples are still generally
preferable to fake. Way too many illustrations here are variants on Products A to
E or Functions A to O. Unfortunately an outrageous example of a bar
chart from a well-known U. S. television set news network (p. 50) seems all
What's not here includes Cleveland dot graphs, histograms and box and building plots
even among the staples of good preliminary statistics courses, let
alone (say) use of logarithmic scale, always one of the first graphical
devices for many sciences. So if you need something with additional
statistical bite or depth, you need to look elsewhere. Naomi Robbins'
excellent, no rubbish Creating more effective graphs
would enable you to go further.
Because in any first edition there are some small slips and exaggerated
claims. 40% is not a majority (p. 5). There is dilemma between number
and percentage on g. 39. Any rule that " bar charts need to have a zero
baseline" (p. 52) is simplistic. It is quite correct that bar graphs
should encode departures from some reasonable reference level. (The
television network dependable should have paid attention. ) But that
reference level could easily be some value not zero, such as parity
between men and women, or the mean of a variable, or 32 certifications
Fahrenheit to separate freezing and non-freezing temperatures. I
disagree that every money amount or per cent should be labeled as such
(p. 90); that is repetitive clutter such as Knaflic rightly deplores. Nor
is it an absolute basic principle that every axis needs a title. If the axis
labels are 2008 to 2015, no one should need " Year" to explain what is
occurring. Far from being " extremely rare" (p. 141), several exceptions
to that principle are included in this book!
An email on style: Within a very beneficial book is an even more useful
shorter book struggling to escape. With regard to my taste, the mindset
warm-ups and little anecdotes in many cases are too spun-out or too trite. Good
images should be presented as illustrations within a good story: a key
point, but not one that required a long chapter with digressions on Red
Using Hood or on Aristotle on drama, or advice from a junior high
school instructor. A tighter copy-editor might have signalled that
" leverage" (used as a verb about 75 times) was too much of an individual
favorite, while " de-emphasize" for " tone down", " utilize" for " use" and
" incredible" for things all too credible are among several other
A simple solution is to by pass and skim: if a book is on images, you can
always just look at the graphics. In this case, Knaflic has written a
useful book that, small details aside, does well what it tries to
do., I'm only like halfway through this book so far, and is actually already massively helped me put together powerpoints or emails that require presenting data., This book has become my right-hand reference for creating reports and presentations that evidently connect their intended story/message. As a market research consultant, I often have to walk that fine line between a data/statistics-heavy report (to please the investigation department), and a higher level, " give me the top 5 take-aways" presentation for mature leadership. Cole has done a great job demonstrating both the how and the why of information exhibits in a way that is clear, concise, and compelling. I am both the researcher and the communicator for having bought and read this book. I hope Cole keeps on writing...! I would suggest this to anyone who is tasked with outlining and communicating data creatively. I promise - you will not be disappointed., Years back I heard about storytelling to provide the communications, that I wished to get through to the audience, But since a financial analyst my main focus was to create the information and present it in nice ways. And as an instructor in Excel Dashboards I used to be more focused on techniques for graphing presented by authors like Edward Tufte and Stephen Few. Nevertheless when I came across Cole's book " Storytelling with data" it added extra dimension to my understanding of how I could get the message to the audience. Finally I understood storytelling, and how it can benefit me as an analyst., The book is well written and the charts are extremely polish. The author has done a great job explaining concepts on all different attributes that make a good story when using data.
I recommend this book to anyone seeking to enhance the way they use and design graphs, as well as those that need to present data to others., Simply skimming the images gave me some insight into why some of my presentations didn't go over as well as they could have. A bit wordy in spots, but still worth the time put in. I'll probably also relate to it later on when I need presentation ideas., A very good preliminary book to the world of storytelling with data and data visualization. You get a few of the science behind why certain data visualizations work without feeling overwhelmed. And, you get some really good takeaways to key in on in your own work. After reading this book (and one or two others), people discovered how much my visualizations had improved.
Cole's blog is excellent resource as well - particularly when she takes a not-so-great chart and makes it really tell the story., EXCELLENT BOOK! Recommending it to anybody who is willing to listen. If they avoid, their loss. I'm increasing my job skills. As good written.
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