iStockBrowsing online recently, I’ve come across a number of useful resources to improve your visualisations. We’ve published before on the benefit of Edward Tufte’s data visualisation rules. As well as guidelines, it’s useful to have the right tools for the job.

Once your expectations rise above the constraints of MS Office graphing options, it can be daunting to find a tool to help your analysts.

Hopefully these few examples help complement our recommended lists of blogs, tweeters & books to develop your data visualisation knowledge

Ideally you want your analysts to be free to creatively recognise the most appropriate visualisation to convey the key learning and then select from a toolbox of tools to find one that makes that easy. Helpfully, Andy Kirk on his Visualising Data blog, has curated just such a collection. This is both a treasure chest of potential tools to explore and nicely designed presentation of options to make the exploration itself a visual experience:

Resources – Visualising Data

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To complement my previous recommendation of Edward Tufte’s data visualisation principles, Ben Jones (on his Data Remixed blog) does a great job of drawing out lessons from a classic on writing. In his blog post, marking the passing of William Zinsser, he usefully summarises the main points from Zinsser’s classic “On Writing Well”. Ben points out how these principles of simplicity, clutter, audience etc directly apply to data visualisation as well. This is well worth reading and applying to your practice (as writer & visualizer):

On Visualizing Data Well

William Zinsser, 92, died last week. Zinsser, author of On Writing Well , the classic guide to writing nonfiction, has been an inspiration to writers and aspiring writers since he first published his manual in 1976. Douglas Martin of the New York Times has written an excellent obituary on Zinsser.

I’m also becoming a fan of Kaiser Fung’s Junk Charts blog, where he shares good and bad examples of data visualisation. Most useful he periodically critiques data  visualisations in publications, to show how they could be improved. Here’s a nice simple example that culminates in a reminder as to the power of (those often under appreciated) bar charts:

http://junkcharts.typepad.com/junk_charts/2015/06/how-to-tell-if-your-graphic-is-underpowered.html

Which leads us on nicely to my final item in this collection. Visual.ly often have interesting content on their blog and this post caught my eye. Drew Skau points out some of the risks of infographics and some undergraduate research on the relative effectiveness of different styles. The embedded SlideShare results are interesting and reinforce the benefits of classic bar chart design:

Exploring the Perception of Bar Charts

published on May 28, 2015 in Visualization The world of infographics has produced a race between designers. The Internet is flooded with hundreds of infographics every day, so those graphics with good design and novelty features have a big leg up against competition in the race for eyeballs.

I hope those resources are useful for you. How are you improving the quality of your analysts’ data visualisations?