Our take on data storytelling
Increasingly organizations are turning to their data to measure, track, report, and ultimately drive growth by having a solid understanding of their market and their customers. But, for real data-driven change to occur, more people need to have access and understand so they are empowered to participate in discussions around data.
2022 is approaching very fast, which means a new year of changes and opportunities! And something we always find interesting and a thought-provoking read is the annual Tableau BI Trends Report. So we were very sad to find out that, at least for now it seems, Tableau paused the project. The last report you can currently access is the one for 2019.
Going over the latest report, which we still believe is very relevant in 2022, we spotted something particularly important. One of the main highlights was that data storytelling will be the new language of corporations.
We couldn’t agree more!
Increasingly, organizations are turning to their data to measure, track, report, and ultimately drive growth by having a solid understanding of their market and their customers. But, for real data-driven change to occur, more people need to have access to and understand data insights so they are empowered to participate in discussions around data. And this is exactly where data stories can shine.
Communicating with stories is a powerful and frequently utilized way for us humans to interact. We’ve been honing the skill for centuries! Today, data stories are an effective way to communicate the insights found within the data that have become an increasing part of our daily lives. With data stories, everyone, whether they are business decision-makers, investors, consumers, or the general public, can easily understand and become participants in discussions about what the data can tell us.
Yet, ‘data story’ remains a term that many people struggle to grasp. What is it and how does it fit into our data-rich world. Despite being the topic of the conversation for some years now, there is still no clear definition, it seems. So with that in mind, we want to share three characteristics that align with Datylon’s interpretation of what data storytelling is.
Table of contents
From data exploration to data explanation
Exploring the data can tell an analyst a great deal. The investigation is often triggered by a question or hypothesis, with the goal to validate or dispel the theory. So, in the data exploration phase insights are mined.
In the next (and often overlooked) phase - the data explanation phase - we package the insights in a way that the data can be discussed. It is in this phase that the true value of the data is unlocked. With data stories, necessary context is added to the insights. This ensures more people can understand and participate in the discussions around data.
By communicating what is found in the data, or in other words, telling the story of the data, the reader is guided towards a deeper understanding of not just what is happening, but why it is important. When the reader fully understands the all-important why, they know how to take action.
Data stories bridge the facts with emotion
It is often assumed that a data story is just another term for data visualization, dashboards, or reporting. Yes, data visualizations do a fantastic job at distilling complex information down to reveal something that would normally not be seen – where patterns and outliers are no longer hidden in a sea of rows and columns. But the problem with leaving communication there is that each person can potentially draw different conclusions from the same chart or graph.
By layering in a narrative and annotations that explain the data insights, and by offering more context, the magic of the data story appears. There, two very distinct worlds of hard data and human emotion start to merge. Figures in a spreadsheet are hard to tell a story with, but when those figures are visualized and explained, they can create a real impact.
Decisions are often based on human instinct and emotion, rather than solely on logic. Therefore, when data is packaged into a story, it allows the facts and logic to be carried across to the influential (emotional) side of the brain where the action is motivated and change occurs with informed decision-making. Messages can be more easily recalled and conveyed based on the audience’s needs and expectations.
Data stories are the final step in the data supply chain
One of the problems faced when working with data is that, since its proliferation, data has often been safely kept in the hands, heads, and spreadsheets of those who are analytical and qualified to handle its complexity. Such data experts are extremely talented in extracting information. But presenting the findings for wider engagement is not always their main focus.
When producing a data story, you take insights off the desks of the data analytics department and publish them. By doing so, you unlock the real value that exists within the data. This step is necessary in order for an organization to be truly data-driven.
And it is within this “final mile” of the data supply chain that Datylon offers solutions, providing a tool that facilitates the creation and sharing of data stories via the Datylon platform. With the Datylon web app, data stories become as accessible as they need to be within organizations and teams. Reports or data stories can easily be organized and even set as templates so they can be edited and updated with the latest data, allowing for truly valuable conversations and informed decisions to take place.
We believe that by providing context alongside clear and compelling data visuals, or in other words creating a data story, even seemingly complex matters can be transformed into something understandable for all.
If our interpretation of data stories conveying information in an actionable way sounds interesting to you, then we would love to connect! Drop us an email to discuss more on how Datylon can help you, and your data, bring about change. Or check out our latest customer stories, to see how others benefit from our digital and dataviz expertise.
What if more people could understand what the data means? That’s the "Big Hairy Audacious Goal" Erik set forth as co-founder of Datylon. When he’s not juggling the many facets of scale-up life you can find him rewind somewhere in nature hiking, biking, running or enjoying the slopes.