Visual energy in data – the art of informed graphics

“Visualisations give us access to actionable insight, we’re wired for visualisations” – Noah Iliinsky

By Rebecca Maserow

What is all this fuss about data visualisation and how can it better my influence through my work? Data visualisation (DaViz) has been described as a “bettering journey from data to information and eventually to insight” (Oren Frank, 2010). At a deeper level, it is “a simple and understandable visual communications approach that abstracts data over time, and describes the relationship and relativity of the essence, cause and dynamics within a data set”.

Driven by technology, data visualisation is rapidly becoming sophisticated and is increasingly sought after. Waldo Leonhardt, a specialist business intelligence business analyst at Saratoga, takes a closer look at how data visualisation, commonly referred to as infographics, can support business analysis.

Graphics as a business communication tool

In the business world, misunderstandings on projects and briefs happen all too often. Organisations tend to over-analyse the document requirements right at the start of projects, resulting in bulky incomprehensible documents (that are seldom read). “Documents are a dumping ground for ideas” and the mess of information makes extracting significance a painful process,” says Leonhardt. He advocates using data visualisations right from the start of requirements gathering to support early analysis. Knowledge can be compacted and communicated as infographics for greater understanding and alignment across a team.

The data detective

David McCandless, author of Information is Beautiful, describes himself as a “data detective”. Likewise, Leonhardt’s role as a business analyst is to “act as a translator between the business problems and IT solutions”. Sometimes tasks start off being very abstract, “the stakeholder has an idea that they verbally try to explain for what they envision. It’s intangible, which is often a challenge”. As a BA, his role is not only to understand the problem behind the business need, but also to communicate the issues and the proposed solution to all stakeholders. Data analysts like David McCandless warns against bias, that the person conducting the research has direct influence over the outcome. Also, be wary of absolute figures, ensure that figures are relational, self-reflexive and honest.

The use of data visualisation should be to improve understanding of core data. People are better able to view, analyse, interact and share the information they need. More importantly, they’re empowered to make informed business decisions.

Juicy data

So what does a “good” infographic look like? Simply put, a good design is one that presents the information in a clear way. David McCandless jokes that the art comes from “getting data good and tight and comprehensive” for what he calls “Juicy data”.

Juicy data, however, does more than to just add aesthetics. It enhances and clarifies the presentation of complex information. Using visual elements well in information display is all about function – what information is being conveyed, and how design enhances that message. Also, who will view, in what context will it be shown, and at what time and place will it be encountered? A text’s unity ultimately lies, as Roland Barthes sharply observes, “not in its origin but in its destination”.

Leonhardt suggests that the more complicated the data is, the better candidate it is for visualisation. He says: “If it’s too abstract or complex it’s impossible for outsiders to draw a picture. To be able to imagine, you must get to the core of that complexity to understand what exactly is needed, and to just focus on that.”

Wired for visualisation

This excitement and energy surrounding visualisation of data begs the question – why is making data graphical so appealing? Kris Holmes, in the fascinating film produced by Edward Tufte Teaching to See, explains that the eye seeks out order – “the eye wants pattern, the eye wants order, the eye wants relative perfection, something that is reliable, that it can count on.” This implies that the brain is more receptive to information that’s presented in a way that’s comfortable for the eye to interpret. Designers are adept as using primary visual systems – namely shape recognition, edge detection, and pattern matching – to present information with the aim of extracting meaning from data.

Afrographique

Ivan Colic’s overview of South Africa’s use of social network on mobile phones, Afrographique

Noah Iliinsky, in Why is data visualisation so hot, builds on the idea of the biological function of the eye and how it reverts to cognitive comprehension agreeing that although naturally “deeper insight comes from deeper study, there’s a lot to be said for quick access and reader engagement.” The benefits of data visualisation is not a tough sell – it makes information sexy, shouts for attention and is easy to consume. More importantly though it aids communication.

You can’t solve it unless you can visualise it

The benefit of Juicy data far outweighs the time-consuming nature of the design process. The information gathered during this journey is insightful and actionable, the problem-based nature of analytics and data means there is a perennial need for deeper understanding and pattern formation.

In this way, data visualisations embodies Einstein’s famous quote “if you can’t explain it simply, you don’t understand it well enough.”

Catch Leonhardt’s talk on The Art of Visualising Requirements at the 2014 Business Analysis Summit Southern Africa (BASSA).

References:
Druckrey, I. Teaching To See
Iliinsky, N. Visual.ly. Why is Data Visualization so hot
McCandless, D. Information Is Beautiful
Rosling, H. Gapminder. TED – US State Department
Oren, F. Marketing Data Visualization

General interest:
Innovation by Design, 2014. In Fast Company Design
Best of the Visualisation Web, June 2014. In Visualising Data
Visual Literacy
Afrigraphique by Ivan Colic

Big Business Joins Social CommunityInter-View Report 2014