Data Visualisation Best Practice – What, Why & How.

By Ian Stuart, Data Visualisation Specialist, Altis Consulting UK

Introduction

What is Data Visualisation best practice, why should I be interested in it, and how do I go about it?  Let us see:

What is Data Visualisation Best Practice?

Designing attractive reports and dashboards, that best help you to communicate stories with data.

That’s the one-liner but there is more to it:  How to choose colour and why, what chart types to use to convey different types of information, how to address accessibility issues, how to lay out a dashboard and how to avoid misleading our audience.  These are just some of the factors and considerations that feed into this fascinating and very important subject

Data Visualisation Best Practice Design is not the same as graphic design or website design – these are separate disciplines that have different rules.

Why should I be interested in it?

We want to convey information to our audiences correctly and in a manner that they can understand quickly and easily. If a report consumer has to spend a lot of time trying to figure out what the report is trying to say or they cannot understand a particular chart type, then you haven’t met the goal of communicating stories with data.

Data Visualisation Best Practice does not arrive “out of the box”. Procuring a data visualisation tool (such as Power BI, Tableau, Qlik or any other) does not guarantee that your reports and dashboards will conform to data visualisation best practice principles.

Data Visualisation tool vendors are not necessarily experts when it comes to data visualisation best practice and we should not rely on them to be so.  Regardless of what the tool generates as default chart types, we generally have the ability to alter the visualisations, reports and dashboards in order to conform with best practice.

Unfortunately, most people have not heard about Data Visualisation Best Practice as a design concept.  We run a poll during a weekly training course we deliver for 50-60 people and the screenshot below is indicative of the weekly poll results.

What training have you had in Data Visualisation Best Practice?

The results are typical of the 2,500+ attendees we have surveyed in that only 5% (on average) have had formal training in this subject and 75% are generally unaware of it.

Without Data Visualisation Best Practice knowledge, a lot of reports and dashboards are:

  • Hard to interpret
  • Misleading
  • Unattractive
  • Inaccessible

Here is an example sourced from a toolset vendor’s web site:

Whilst this is certainly an attention grabber there is much that requires attention.

Overall, can you understand what the report is showing you, what the key messages are and what actions you need to take?  How would you like to interpret this on a daily basis?

How do I go about it?

Learn some principles

Altis offers a Data Visualisation Best Practice training course in which we cover the following agenda centred on understanding the story we are trying to tell:

 

The training also considers data visualisation best practice in relation to Accessibility & Mobile Devices.

Learn how to apply the Principles

We need to have a process for design and development that ensures that the above principles have been considered and that any deviations are justified. Our training delves into design and development techniques, rules and guidelines that are based on the principles.

Dependent upon the software we are using we may be able to set up templates or themes to help us with this process.  My colleague Roger Light has written an excellent blog covering exactly how we can do this in Power BI.

We advocate for an iterative design and development process with plenty of opportunity for frequent feedback.  The process should embrace the fact that stakeholders will change their minds and ask for new things as and when they start seeing their reports come to life.  We should show our customers and peers our design as it progresses and listen carefully to what they have to say.

We also need to be equipped to justify our design decisions if needs be, and to be able to knowledgably steer our stakeholders away from suggestions of introducing something that is not good practice.

Here is an example of how one report design moved from initial whiteboard ideas through to the final article after passing through multiple iterations:

 

 

Practice, practice, practice

Whilst learning the principles is possible in a day, mastering them and embedding a process that works for you and your organisation will take time.  Initially we will need help to critique our designs until we have built a culture of good data visualisation design.

Practice will not make perfect as there is always something to improve. Let’s look at an example of good practice and point out some elements:

With this design the user can easily understand what the report is showing, know what the key messages are and what actions they may need to take.  Interpreting this on a daily basis should be simple and fast.

If data visualisation best practice was something that you previously hadn’t thought of, then I hope this brief introduction has motivated you to want to learn more about creating attractive, meaningful and useful reports that best communicate the story with data to your audience.

Connect with us if you’d like to learn more about how we can help you be successful with Data Visualisation.

 

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