What is the primary purpose of storytelling in data science?

The primary purpose of storytelling in data science is to communicate complex findings and insights effectively. In this context, storytelling involves taking the results of data analysis and presenting them in a manner that is accessible and engaging for the audience, whether they are stakeholders, team members, or clients. By using narratives, visuals, and examples, data scientists can transform raw data and statistical outputs into compelling stories that resonate with people, helping them to understand the significance of the data and facilitating informed decision-making.

This approach contrasts with merely showcasing programming skills or impressing others with technical jargon, which can alienate or confuse audiences who may not have a technical background. Additionally, highlighting personal achievements does not align with the core goal of making data-driven insights actionable and meaningful to others. This unifying goal underscores the critical role of storytelling as a bridge between complex analytical work and effective communication.