Here is the presentation I did to my colleagues to explain what my day to day job is, and why visualisation is an important step to any department of a company.
Before you start multi tasking thinking that this presentation is not for you, keep in mind that data journalism is a mindset, not a finality, therefore everyone can do it. You included!
Not One, But Many Definitions
The type of data visualisation to use will vary with the audience, the message and indeed the dataset. You will find different types of visualisations, as in:
1. R type graphs, with no fancy adds up (no icons or barely). It tells a story with a short caption and a chart. I used a Financial Times visualisation in my example (the purple square). In a single chart you get a story: The analysis of the EU referendum vote shows that a large share of Leave voters came from areas with a low number of degree-educated people.
2. Lifestyle visualisations, with a crafted design but few data, as illustrated here in the green square. It's the opposite of the R type graph, the story doesn't rely on a data display but on the illustration.
3. Tableau Dashboards, are both fancy and relying on data but usually lack storytelling, here in the yellow square.
Are You After a Unicorn?
Each visualisation should find a space in one of those categories. Usually relying on data, it can also use design to tell a story. There is not one vision of data journalism but a broad range of paths to adapt to any strategy.
Many arguments can be invoked to introduce data journalism in every department of a company. Widely used in marketing, as it's an entertaining way to convey quantitative information, it also finds its utility for internal communication. Simplify reports, dig a story out of series of dry numbers, or get an idea through to a busy and short attention spanned audience, nothing is impossible to data journalism!
A Striking Example: The Billion Dollar-o-Gram by David McCandless
I love that visualisation because thanks to a well design but simple visualisation you quickly get the big picture of a complex dataset: the 2009 US budget
And with that second image you can link 2 types of information: the cost of the financial crisis compared to the annual budget of the US. The perspective induce the reasoning, and that's what good data journalism looks like.
Do What it Takes - But What Does it Take?
Now the real question is: How do we build a good storytelling?
Unfortunately there is no magic recipe. Don't get desperate though, I have a bunch of tips that may help you.
The Urinal Analogy
Let's see it from another perspective. Can you see the urinal below? How much money do you think it's worth?
Not that much, isn't it? A plain white urinal cost between £20 and max £100 (with gold leaves - just kidding).
And if now I was to give you a bit of context: the original of that urinal was presented at the Parisian Salon des Indépendants in 1917 by Marcel Duchamp, widely seen as the father of conceptual art. If you wish to read the complete story, it's here.
Now that you have a bit more context, how much money do you think this urinal is worth? A lot more I guess...
Below the answer.
Don't Throw a Urinal at Your Audience's Face
What is the common point between the story I just told you and data journalism?
Your data is just like that urinal: you think it's a piece of art, but without any context, your audience will see it as a banal urinal.
It's not enough to tell people that your dataset is worth it, you need to prove it. How? By giving it a bit of background,
1. Choose a dataset or a message: in marketing you would choose a message first and then find a dataset that backs it up. In journalism, you may want to analyse a dataset first and then choose an interpretation that fits it. In both cases, the first step is to set your mind on a clear objective.
2. Contextualize your dataset: you may have spent hours on it but remember that your audience has not. Always assume that your audience has less knowledge than you do. Better saying things they already know and refresh their memory, than skip a whole part of the story and miss your goal.
3. Compare your data: to the same dataset in the past / against another trend or another brand / etc
In one word, put it into perspective. Choose carefully how though, as it's that comparison that will drive your audience to your message.
Visualisation is about Empathy
Don't inflict to your audience what you find difficult to cope with yourself.
Use colors to underline your point: red is bad, green is good
Order values: make it easy for your audience to understand your message
Don't forget titles and captions
The Visual Brain
Stimulate your audience visual cortex by using icons. I like using The Noun Project, but a Google search does just fine too.
Get to the point
I know you've been working hard to gather all that info and you really wish to talk about everything. Unfortunately drowning your audience with details will not help your message getting through. Select your main take-away, what your audience should remember after your presentation / reading your infographic, and twist your argumentation around it. Personally I like keeping 1 idea per slide when it comes to presentation.
I hope that post helped you to understand a bit more about data journalism and data visualisation. Remember: practice makes perfect!