Turning Expansion Engines into Metrics
When companies separate the engines (and measure them appropriately!) NRR stops being a flattering mirror. It becomes a diagnostic tool, meaning executives finally see the underlying patterns shaping long-term sustainability.
The Three Engines of Subscription Expansion
For any enterprise subscription business, whether you sell software, research, data, intelligence, workflow solutions, or a mixed portfolio, the distinction between expansion engines matters more than most leaders realise.
Why Net Retention Is Not a Strategy
Executives misinterpert Net Revenue Retention when it is treated as a target in itself, a universal truth about the customer base, or the cohort quality is taken for granted. The truth is, NRR becomes useful when executives treat it as the headline of a story rather than the whole plot.
From Chaos to Clarity: Sustaining the Culture of Data Freedom
Rules are static. Culture is alive. In this final instalment of the series, we focus on the cultural layer that ensures long-term success of self-service BI.
Governing the Commons: Feedback, Incentives, and Light Touch Control
is about designing the environment so that the easiest way to work is also the most responsible.
Structuring Freedom: Best Practices for Report Builders
Part three explores specific design and build practices that allow report creators to work freely without overloading the shared semantic model or dragging the capacity to its knees.
The BI Commons: Lessons from Systems Thinking
We aim to preserve the creativity and speed of self-service BI, while avoiding the chaos that comes from having no rules at all.
Freedom, Chaos, and the Need for Governance
Absolute freedom (in society or BI) sounds noble but rarely works without governance. Data democratisation is no exception.
Copilot-Focused Model Enhancements
Using AI Schema & Verified Answers to get the most out of your Model.
The Magic of Tabular Editor
Tabular Editor doesn’t just let you tweak the model more efficiently, it actively improves your working life.
Streamlining & Simplifying Your Data Model for Copilot
It's time to tackle what might be the most underappreciated aspect of a semantic model: simplicity.
Do You Really Need a Semantic Layer? It Depends, But Probably Yes
In Power BI, which I work with extensively, the semantic model isn’t optional, it’s built in.
Semantic Model Foundations - Giving Copilot A Fighting Chance
This article walks through the boring, beautiful basics of semantic model hygiene.
Field Notes from Building a BI Platform on AWS and Power BI
This is not a how-to guide. It’s lessons I learnt the hard way, sometimes messy, occasionally political but hopefully useful.
Plato, Democracy, and the Data Delusion
Plato distrusted democracy because he believed it gave people the illusion of wisdom. I’ve seen dashboards do the same thing.
Socrates in the Boardroom: Why BI Needs Better Questions
The numbers speak, but only the questions make them meaningful.
Confidence Is Not Competence: Why AI Needs Critical Thinking
In business, confidence can often be mistaken for competence.
Why Microsoft Fabric Is the Ideal Platform for AI-Ready Semantic Modelling
Microsoft Fabric doesn’t just support semantic modelling, it elevates it.
Why Your AI Strategy Needs Robust Semantic Modelling
Have you ever had a stakeholder ask why you can't just throw an LLM at your data? I have—and it misses a crucial point. AI might be powerful, but without business context, it’s just guessing. That’s where semantic modelling comes in. In this article, I unpack why semantic modelling is essential for trustworthy, scalable AI — and how it sets the foundation for real insight.