Best Practices

Best Practices in Data Visualisation:  A Review of ‘Storytelling with Data’ and my Before and After.

One of the biggest mistakes I made when applying for my position at the data school (well at least in my opinion) was that I made my visualisations far too complicated. I fell into that trap that I think all Tableau newbies fall into. I was so impressed with all the things that I could do with Tableau, that I just wanted to cram in everything I had done into one dashboard.

The first week in the data school was all about best practices in data visualisation and one of the books that I read was ‘Storytelling with Data – a data visualization guide for business professionals’, written by Cole Nussbaumer Knaflic. Here is a review of that book:

Storytelling with Data: A book review

‘Storytelling with Data’ is a great book for anyone who is just starting their data visualization journey. The basic gist of the book, is to keep your visualisations simple and to the point, a message that has now been thoroughly homed in, via this book and every other form of data visualisation best practice advice I have received.

The book is broken down into 10 chapters, of which 5 make up what I would consider the the core of the book. These teach you how to put your data into context, guide you through choosing effective visuals, teaching you that ‘clutter is your enemy’, how to focus the attention of your reader and to ‘think like a designer’, using size, colour, positioning and most importantly, simplicity to make an effective visual. Chapter 6 walks you through how to tie a story together and the rest put the lessons learned in the first 5 chapters into play.

What I appreciated most about this book, is that it practices as it preaches. Storytelling with Data is written well, in a very easy to follow manner, thoroughly driving home the points that it wishes the reader to take home. Because the book implements all the highlighting or rather ‘leveraging preattentive attributes’ that it describes, it makes it very easy to get all of the important information, without having to take too long to read the book and also makes it easy to find the tips you have learned and want to revisit.

My second favourite things about this book is the graphic examples. Nothing brings home the point about best practices of visualisation better than a visualisation! In particular I enjoyed the before and after visualisations, which not only brought home what I could be doing better and also became a fun game towards the end, seeing how much I had learned and if I could find all the elements that needed improving! The book even gives you a treasure trove of great sources of ‘inspiration through good examples’ by data viz gurus.

In closing, this book is great data visualization noobs like me. It gave me a fresh, concise and effective way to tackle the data visualisation challenges that have and are still to come my way!

In the second week of the data school, we were asked to make a ‘reviz’ of the data we had submitted for our initial applications. I was able to apply so many of the tips I had learned from ‘Storytelling with Data’. Have a look for yourself here:

Link: Before


Link: After


The Data Viz Community and Resources to get you Started


This article is recycled from the blog I wrote at the data school (also included as one of the resources for learning tableau), although slightly updated. But in building the blog from scratch, it really is the best place to start. So here it goes…..

I still consider myself relatively new to the data visualisation scene. It has, after all, only been 6 months that I have been using Tableau and Alteryx. Whilst I still have a long, long way to go, I have learned a lot at my time at the data school (and on my first placement). Now, while the training I received from the Information Lab, was second to none, one of the things made me really love the data viz world, is the data viz community. The Tableau community in particular is incredibly warm, welcoming and ready to help you learn.

If you aren’t already, get on twitter and get on tableau public. Twitter has lots and lots of ‘lists’ to show you good data viz people to follow and on tableau public, aside from showing off your own work, you can find people whose style you like, follow them and have a constant source of inspiration!

Here are a few of the websites, blogs and books I found that really helped me gets started and ones that I have found later on in my journey that I wish I had found earlier.


Websites and Blogs:


  • ‘Storytelling with Data – a data visualization guide for business professionals’ by Cole Nussbaumer Knaflic – book review soon to come!
  • ‘Golden Rules for Great Business Charts – 50 practical tips for business professionals’ by Laszlo Zsom
  • ‘Now you see it – Simple visualization techniques for quantitative analysis’ by Stephen Few
  • ‘The Truthful Art’ by Alberto Cairo

This is of course, just the tip of the iceberg. There is so much help out there on the interwebs to get you started and so much to keep challenging you through your data viz learning experience.

Hope this helps!


An Introduction

Hi and welcome to my data blog.

About 8 months ago I started my data journey. I joined the Data School at The Information Lab and in four quick months, I went from knowing next to nothing about effective analytics, Tableau or Alteryx, to, to my great surprise, being a functioning consulting analyst. Of course, as part of the Data School, I had the privilege of  being taught by some of the best Tableau Zen masters and Alteryx Aces in the field, but what I had not expected was the warmth and wealth of knowledge imparted by the Tableau and Alteryx communities. Writing this blog,and sharing what I have learned along my journey so far,  is my way of giving back to the community and if it helps at least one person, the way the blogs, videos and articles that others have written helped me, I will have accomplished my mission.

The first few posts might be slightly stolen from my blog on the Info Lab Data School page, but they do serve as a good basis for starting out with data analysis, so watch this space!