# Data Modelling & AI : A Deep Dive into the Future of Tableau with Kirk Munroe

> This is content from just-tim, the data-and-analytics channel by Tim Ngwena (formerly 'Tableau Tim'). Tim has 12+ years of hands-on BI experience and covers Tableau most of all, plus Power BI, Looker, Hex, SQL and data modelling, the analytics industry, and the craft of doing the job — always tool-agnostic and honest about the trade-offs.

- **Author:** Tim Ngwena (just-tim, https://just-tim.com/about)
- **Published:** 2024-10-03
- **Format:** Video · 123 min watch · transcript available
- **Topics:** Data prep, Tool strategy, AI & ML
- **Tools:** Tableau (data modelling, lod expressions, prep, pulse, relationships, row level security)
- **Canonical:** https://just-tim.com/posts/data-modelling-ai-a-deep-dive-into-the-future-of-tableau-with-kirk-munroe
- **Watch:** https://www.youtube.com/watch?v=udhL_jnWPSk

I sit down with Kirk Munroe, esteemed Tableau community member and author of a book on data modelling, for a long-form conversation. We dig into why relationships changed how we should work in Tableau, the gap between report builders and business users, the realities of writing a book versus making video, and where Tableau is heading with AI and features like Pulse.

## Key takeaways

- Joins explode and expose your data while relationships preserve the ability to answer questions without inflating row counts, so questions like running totals of open tickets become instant rather than painful.
- A small number of people building high-performance published data sources, ideally with row-level security baked in, makes Tableau dramatically faster and easier for everyone else and lets you create a single Pulse metric instead of many.
- Before touching the data, ask to see the application that generates it, because business rules usually live in the application's mid-tier and never make it into the extracted data.
- Not everything needs to be pushed back to the data engineering team; last-mile analytics in Tableau (like filtering out internal warehouse transfers) keeps you agile and saves costly engineering time.
- Understanding why INCLUDE/EXCLUDE don't behave as expected is the best route into genuinely grasping Tableau's order of operations and what being 'in the view' means.

## Chapters

- 0:02 Channel update and what's coming
- 1:06 Introducing Kirk Munroe
- 3:36 Kirk's journey from Cognos to Tableau
- 9:56 Staying passionate about data
- 14:30 Relationships versus joins
- 18:28 Last-mile analytics and the engineering gap
- 23:46 What readers gain from the book
- 30:04 Writing a book versus making video
- 42:01 AI transcription and blogging ethics
- 48:34 How to know you need relationships

Watch the full video, read the transcript and use chapter deep-links on the page: https://just-tim.com/posts/data-modelling-ai-a-deep-dive-into-the-future-of-tableau-with-kirk-munroe

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just-tim — Data and analytics, with a point of view. · https://www.youtube.com/channel/UC7HYxRWmaNlJux-X7rNLZyw · https://twitter.com/TableauTim · https://www.linkedin.com/in/timngwena