Decision Intelligence: Data Stories

In this course, instructor Franz Buscha explores the critical lessons behind some of the most famous data stories to equip learners with the non-technical skills needed to improve decision-making, data interpretation, and communication. Learn via engaging examples and real-world scenarios. Discover how to navigate challenges such as causality, ethical considerations, flawed models, and declining data quality. Delve into the importance of clear storytelling, stakeholder communication, and ethical data use to ensure insights lead to impactful and responsible decisions. When you finish this course, you’ll be able to analyze data stories, evaluate models, apply best practices, design strategies for continuous model improvement, and more.

Learning objectives
Analyze real-world data stories to identify the key lessons and decision-making principles, demonstrating an understanding of their impact on business, policy, and individual contexts.
Evaluate data-driven models and decision-making processes, identifying potential flaws, ethical challenges, and areas for improvement in predictive analytics, data communication, and survey methodologies.
Apply best practices in data interpretation and communication by using storytelling techniques to clarify insights, highlight risks, and tailor presentations to diverse stakeholders.
Critique the ethical implications of data experiments and predictive modeling, ensuring that data-driven decisions are both transparent and socially responsible.
Design strategies for continuous model improvement, stakeholder communication, and survey enhancement, integrating lessons learned from notable data stories into their professional workflows.