16 August 2024

🧭Business Intelligence: Perspectives (Part III: From Data to Storytelling I)

Business Intelligence Series
Business Intelligence Series

Data is an amalgam of signs, words, numbers and other visual or auditory elements used together to memorize, interpret, communicate and do whatever operation may seem appropriate with them. However, the data we use is usually part of one or multiple stories - how something came into being, what it represents, how is used in the various mental and non-mental processes - respectively, the facts, concepts, ideas, contexts places or other physical and nonphysical elements that are brought in connection with.

When we are the active creators of a story, we can in theory easily look at how the story came into being, the data used and its role in the bigger picture, respective the transformative elements considered or left out, etc. However, as soon we deal with a set of data, facts, or any other elements of a story we are not familiar with, we need to extrapolate the hypothetical elements that seem to be connected to the story. We need to make sense of these elements and consider all that seems meaningful, what we considered or left out shaping the story differently. 

As children and maybe even later, all of us dealt with stories in one way or another, we all got fascinated by metaphors' wisdom and felt the energy that kept us awake, focused and even transformed by the words coming from narrator's voice, probably without thinking too much at the whole picture, but letting the words do their magic. Growing up, the stories grew in complexity, probably became richer in meaning and contexts, as we were able to decipher the metaphors and other elements, as we included more knowledge about the world around, about stories and storytelling.

In the professional context, storytelling became associated with our profession - data, information, knowledge and wisdom being created, assimilated and exchanged in more complex processes. From, this perspective, data storytelling is about putting data into a (business) context to seed cultural ground, to promote decision making and better understanding by building a narrative around the data, problems, challenges, opportunities, and further organizational context.

Further on, from a BI's perspective, all these cognitive processes impact on how data, information and knowledge are created, (pre)processed, used and communicated in organizations especially when considering data visualizations and their constituent elements (e.g. data, text, labels, metaphors, visual cues), the narratives that seem compelling and resonate with the auditorium. 

There's no wonder that data storytelling has become something not to neglect in many business contexts. Storytelling has proved that words, images and metaphors can transmit ideas and knowledge, be transformative, make people think, or even act without much thinking. Stories have the power to seed memes, ideas, or more complex constructs into our minds, they can be used (for noble purposes) or misused. 

A story's author usually takes compelling images, metaphors, and further elements, manipulates them to the degree they become interesting to himself/herself, to the auditorium, to the degree they are transformative and become an element of the business vocabulary, respectively culture, without the need to reiterate them when needed to bring more complex concepts, ideas or metaphors into being.  

A story can be seen as a replication of the constituting elements, while storytelling is a set of functions that operate on them and change the initial structure and content into something that might look or not like the initial story. Through retelling and reprocessing in any form, the story changes independently of its initial form and content. Sometimes, the auditorium makes connections not recognized or intended by the storyteller. Other times, the use and manipulation of language makes the story change as seems fit. 

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Koeln, NRW, Germany
IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.