Data Storytelling in Presentations

Data is powerful and has always been a necessary part of a presentation. But it is not always that every person in the audience will be interested in the data and analytics, or will understand it the way it has to be.

Data can be in any form and of any complexity. So for those among the audience, who find it difficult to read the data properly, it can be a turn-off and may lead to losing their interest, which definitely is not what a presenter wants. So like the other elements of the presentation, i.e. the content and the visuals, the data has

to be presented in a certain way, such that it is readable, and moreover, understandable. Data is essential, but its role is beyond that. As the visuals and the content is used to tell the story, data too can be used for the same.

data presentation

The data stories are better at explaining the important things related to the data, like why and how the data changes with time. Here visualization comes into action and helps in exploring the data in an effective manner.

Though storytelling is a process used in the field of data analysis and data science, using data storytelling in presentations has also been effective for the success of a presentation.

Even though data storytelling has become so important, there are no specified practices for the same. But like every storytelling is comprised of some important elements, data storytelling is constituted of the following:

1) Authentic Data: Most important and the prime thing, in storytelling, is the data, of course. Great stories come from your own experiences, and likewise, the data stories also are great when driven from own data. But the data used for making the charts and graphs, or used otherwise in a presentation, has to be authentic and correct, as it is helpful in building trust among the audience. The data should be informative enough, such that it is capable of answering the questions of the audience. Manipulation of data and its misinterpretation is a common thing, so along with its accuracy, the source of the data must be credible.

2) Narrative: Like every story has a narrative, data storytelling also needs one. The narrative is responsible for the interesting beginning and the successful end of a story. It organises the data into the time as well as conceptual sequence, such that the visualisation is properly used to tell a story.

The narrative of a graph can be based on the changing trends, rankings, comparison, or a relationship between the data. It is helpful in connecting the dots and producing a meaningful story out of it. The data must be represented in an easy-to-digest manner, and it must help the audience with the process of decision making. All in all, a narrative is responsible for setting up the context and put everything into place for the storytelling.

3)Visualisation: Visualisation of data makes the data attractive, more understandable and memorable. For the visualization of data in the presentation, charts and graphs play the most significant role. Charts/graphs are comprehensive and can represent data of any complexity. But there is a difference between creating a chart or a graph, and make it tell a story. While building the graphs and charts, in order to tell a data story, you need to work on its layout, the colours used in it, and its typography.

The layout must compliment the graph, and the colour scheme must be planned according to the entire theme of the presentation, and the data, of course. You should not use more than six colours in a graph, as it can cause confusion. On the other hand, to use the typography in the chart, the text must be divided into categories like the title, subtitles and labels, and the size and the colour of all must be selected accordingly. Though the text is equally important, you can use icons to eliminate too much labelling.

Data-driven content is always considered to have high quality and value., and increases the credibility of the presentation. For the presentations that are shared online, data stories are the most helpful in terms of assisting the audience with a better understanding of data.

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