As your business continues to collect more and more data over time, the need to extract as much value from it as possible becomes much more significant. The unfortunate truth, however, is that often the value in data remains hidden and rarely sees the light of day. Arguably, the real reason why, so often, the value in data remains hidden is because companies don’t know how to effectively extract the data and translate it into meaningful insights that aid the business decision making process. In addition to this, companies that do extract their data and uncover meaningful insights successfully, commonly fall at the last hurdle; this being communicating the insights to the wider business in an effective way.

In a 2009 interview, Google’s Chief Economist Dr. Hal R Varian specified, “The ability to take data – to be able to understand it, to process it, to extract value from it, to visualise it, to communicate it – that’s going to be a hugely important skill in the next decades.”

When we fast forward to today’s date, the need to communicate insights from data is still a particularly prevalent challenge for many organisations. Furthermore, as the demand for self-service analytics and business intelligence tools continues to increase, so too is the demand for skilled Data Storytellers and Scientists. A quick search on LinkedIn reveals the growing popularity and demand for Data Storytellers and Scientists, with many being recruited into larger firms that have vast amounts of data to make sense of.

In recent years, if a business leader or head of department needed to communicate using data, often they will have wheeled in their flip chart with static graphs and tables, together with an uninspiring presentation containing endless amounts of uninteresting information. Unless the presentation included statistics that show profitability is on the increase or that sales revenue is at a record high, the likelihood of their audience being engaged with the presentation is very slim. However, the main problem here is not that the data is erroneous or wrong, the problem lies within the way the data is being communicated and that’s where we begin to look at a very simple solution – data storytelling.

The term data storytelling has been around for a while now, but, the problem is that the term is often overused or is associated with something entirely different. We commonly hear the words dashboards, visualisations, infographics and data presentation being associated with the term data storytelling, but they are all completely separate things.

In reality, data storytelling is “the process of translating data analyses into layman’s terms in order to influence a business decision or action.” A post written by Brent Dykes back in 2016 highlights and outlines the three main elements of data storytelling in a very clear and easy to understand way. Dykes says, “data storytelling involves a combination of three key elements: data, visuals and narrative.”

When these three key elements are combined, data stories come alive. Like a novel or story, a narrative is used to connect and consolidate a series of events into a clear and succinct sequence. Then, when visualisations are brought into play, they engage and captivate your audience and help to bring out data that would otherwise remain hidden in static graphs and tables. Combine these two components with data, and you have the foundation to a very effective data story.

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Posted in Big Data

June 4, 2018