For software developers wishing to work in Big Data, what do you think are the most important technical skills or certifications to have?
I responded with:
Technical skills? Any, non-issue.
People skills: storytelling, visualisation, rhetoric.
Business skills: understanding, patience, domain knowledge
which resulted in David asking me to expand on my response, so here goes…
These come and go – there is always a new technology / approach / technique that we can throw ourselves into. Expanding one’s horizons technically is almost always useful – it helps evolve the way we think about problems, how we attempt to solve them, and consolidates our core skills – but a list of specific technical skills would is almost endless. Besides, a fool with a tool is still a fool – there is danger of amassing a huge arsenal without the requisite understanding to use the tools (or skills) wisely.
Good data science, and the best use of Big Data, comes down to analytics… and analytics is pointless until an audience – from one to one billion, depending on your purpose – understands something of what you do. That is, once you have analysed your data, and discovered insights of value, your challenge is to communicate these effectively to your audience. All the technical skills in the world are now useless, if you can’t tell a story; so storytelling is the most important skill.
And storytelling is tough, because we technicians are not used to it; it’s one thing to regale friends in the pub about something amusing that happened that day, but it’s another to convey complex or subtle ideas to a largely unknown audience. The best way I have found to improve my storytelling is the use of visual aids; rich, interactive data visualisations which allow me to make my stories interactive. I can tell a linear story, presenting a series of visualisations, at the start whilst my audience is barely engaged – then as they warm up, and interact, we can go “off piste” and explore data together. This audience participation drives involvement, appetite and understanding; and it’s understanding that we Data Animators should be aiming for.
Finally, I suggested that rhetorical skills are valuable; the ability to form a compelling, persuasive argument is essential in fact-based storytelling. The storyteller needs to persuade the audience of the validity of the analysis that has taken place, of the findings and conclusions, and – usually – of the need for further analysis and investigation. The great thing about information emerging from analysis of data, is that it’s almost limitless – there is always another area to explore and further insights to discover.
Discovering interesting stories – those which matter to the audience, where the themes, narrative and outcomes matter to them – requires an understanding of what the audience wants. In my business, that means that I need to understand the pressures, challenges and opportunities facing senior managers in large retailers and consumer goods companies. So it’s vital to understand what drives and motivates my audience; what their fears and hopes are, and what information they require in order to understand a problem, or an opportunity, so that they act upon it.
That action is what I’m looking for – because it’s the reason they hired me and my colleagues in the first place – so I need to remain patient in explaining observed patterns, possible and probable causes and interesting or surprising correlations. Engaging an audience also means taking on prejudices, assumptions and corporate myths that grow from the learned behaviours that we all carry. This is an interesting challenge, because on the one hand I’m arguing that domain expertise is necessary – in order to understand the audience, their world, their language and needs – and on the other I’m suggesting that being inside that world limits our ability to look at it with new eyes. I’m not a retailer – I have never worked in retail or consumer goods – and I have worked hard to develop relevant knowledge and familiarity, but being outside that world lets me look in and ask the dumb questions that expose frail answers. There is a balance to this, which
Which brings me to the one skill I missed off my original response, and probably the best way of summing everything else up – the essential skill for the Data Animator; curiosity.