Show Notes
In this episode of the Agile Data N’ Info Podcast, host Shane Gibson sits down with Kat Greenbrook, founder of Rogue Penguin, author of The Data Storyteller’s Handbook, and an expert in data visualization and data storytelling. In this episode, the conversation explores the intricate world of data storytelling and the ABT (And, But, Therefore) narrative framework. Kat explains how the ABT model operates as a flexible framework that makes audience engagement and clear messaging first-class citizens, extracting meaning out of complex analytics and linking it directly to actionable business goals. By focusing on simple narrative structures and audience motivation rather than just overwhelming numbers, the ABT framework ensures that your data communication remains highly impactful and clear enough to drive real business change. The discussion also dives deep into the complexities of visual communication, clarifying the crucial role of separating data exploration tools from storytelling. Kat breaks down how adopting high-contrast pivot words—like “but,” “however,” or “despite”—prevents audience disengagement—like the dreaded “death by and”. This approach achieves clear, captivating communication by definitively shifting the direction of the narrative to highlight core business challenges and solutions. Whether you are curious about how to weave the ABT framework into your everyday work, how avoiding “chart vomit” can actually strengthen your message, or want to learn why dashboards should never be confused with data stories, this episode is packed with valuable insights for data practitioners. You can get in touch with Kat via LinkedIn or at https://www.roguepenguin.co.nz/ Buy Kat's new book "The Data Storyteller's Handbook" on Amazon.
If you want want to read a summary generated with GenAI, head over to: https://agiledata.info/i/203810968/google-notebooklm-briefing
If you want to download the transcript for the podcast, head over to: https://agiledata.info/i/203810968/transcript
Listen to more podcasts on applying Agile Data patterns over at https://podcast.agiledata.io/ Read more on the Agile Data Way of Working over at https://AgileDataGuides.com/
If you just want to talk about making magic happen with agile and data you can connect with Shane @shagility on LinkedIn.
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In this episode Shane Gibson sits down with data modeling veteran’s John Giles and Remco Broekmans The conversation explores the premise of democratising data modeling through AI, centered around a paper published by John regarding where AI can and cannot add real value. The group highlights the critical importance of conceptual and context data modeling, stressing that business terms and definitions must be established upfront before looking at physical source tables. They strongly critique the anti-pattern of placing humans “at the end of the line” merely to rubber-stamp automated outputs, arguing instead for an “AI-in-the-loop” approach where technology serves strictly as an assistant under human direction. The discussion also dives deep into complex real-world scenarios where automated tools fail—specifically when physical data or source systems do not yet exist. John shares extreme edge cases, such as establishing a brand-new government department from scratch based on a vague Act of Parliament, unifying over 70 distinct healthcare organisations into a single model, and modeling evolving visions like the Australian wool industry. Remco breaks down his multi-agent ELM framework, explaining how introducing deliberate manual friction points between LLM tasks keeps human modelers in control and why model-storming workshops, human trust, and organisational culture are far more vital than push-button automation. Whether you are curious about conceptual modeling techniques, how to effectively integrate “AI in the loop” while avoiding push-button modeling pitfalls, or strategies for aligning business definitions across complex organisations, this episode is packed with valuable insights for data professionals.
Raw and unedited Top 3 things:
Raw and unedited Top 3 things:
Raw and unedited Top 3 things:
Raw and unedited