The Art of Data Storytelling: How to Make Your Data Impactful

Data is everywhere: whether you choose a new location for your business or decide on the color to use in an ad, data is an invisible advisor that helps make impactful decisions. With quite a number of resources to choose from, data is becoming more accessible, day by day. But as soon as it has been collected, one inevitable question arises: how do I turn this data into insights that can be acted upon?

In the wake of the big data bang, many mistakenly thought raw data to be essential for their business development, which is only partially true. Such a misbelief often leads to frantic investments in data science, which are, however, unlikely to bear any results. Analyzing data and turning it into something comprehensible is only half the battle, while actual insights depend on the way data is treated after being processed. 

That’s when data storytelling comes in. Whether you are in a leading position, a data engineer, an analyst, or a marketing specialist, making the right data-driven decisions is only possible when your insights are logical and relevant. 

Storytelling in general is one of the most ancient ways in which people communicate and share information. The oldest written story in the world, which is The Epic of Gilgamesh, was written in 2000 BC. Since then, the art of storytelling was developing and evolving, becoming as natural as breathing. 

data visualization consulting Today, sharing information is hardly possible without converting data into a story. Data analysts can take their cue from writers, who never serve plain facts but spice them up with characters’ reasoning, motivations, conflicts and resolutions, and apply this approach to raw data. Visualize with BI tools, which are becoming more accessible with the rise of specialized providers of data visualization consulting , and you can create a complete story. 

So data storytelling is not only about getting to know what’s going on, but about understanding why this is going on and what can be done about it. That’s when it becomes clear that not all data is equally valuable, and some of it can even be completely useless. That’s why choosing data sources wisely and being able to extract meaning from them is a challenging yet indispensable step in any data-related journey.