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Practical perspectives on data governance, Microsoft Fabric, Power BI and analytics strategy for UK organisations.
Are your people happy? The first question in any Data or AI project
A shopping list of features was a slow way to waste money. A shopping list of AI ideas is a fast one, because the tools now say yes to almost anything you point them at. The discipline has to come from the questions you ask before you start.
Forecasting and demand planning on the data you already have
Most forecasting projects stall not on the method but on a misbelief that the data is not good enough yet. In practice, a straightforward trend model on clean historical data outperforms a sophisticated model on data nobody trusts. And you already have the historical data.
ODBC to ADBC in Power BI: what's actually changing
Microsoft is moving Power BI and Fabric off embedded ODBC drivers and onto Apache Arrow-based ADBC. Here's what's changing, who it affects, and what to do about it.
Where a data partner adds value alongside a team that already knows what it's doing
Bringing in outside help is not an admission that your team can't do the job. It is often the only way to close a gap they were never resourced to close on their own.
Build it in-house or hand it to a partner: the honest split for a data platform
Not all data-platform work should be outsourced, and not all of it should be kept in-house. Here is the line we would draw, and why.
Why We Never Let Anyone Touch the Bronze Layer: Immutability, Replay and Incremental Data Quality
Why an immutable raw layer, a genuinely replayable pipeline and treating data quality as continuous rather than a one-off project are the three principles that decide whether a platform ages well.
Start with the decision. Then choose the AI framework.
A good AI framework can still produce the wrong work. The useful starting point is the decision the organisation needs to make.
Power BI on Business Central in practice: pitfalls, embedding, and upgrades
The pitfalls, mobile reporting, embedded dashboards, and what actually happens at upgrade time: the practical realities of running Power BI on Business Central once it's live.
What AI can’t do for a mid-market business, and where it goes wrong
The most expensive AI mistakes are not technical failures - they are buying something AI cannot actually do in your situation. Understanding the genuine limits of the technology is more useful, right now, than any capability list on a vendor slide.
What good Azure data engineering looks like when it is running well
Most people only notice data engineering when it breaks. Here is what it looks like when it is done properly, so you know what you are paying for.
Getting your Business Central data into Power BI: the options
Business Central holds a substantial part of your operational truth: sales, purchasing, inventory, and more finance. Power BI is where that truth becomes visible and usable. Getting it right first time avoids a category of report reliability problems that are genuinely hard to unpick later.
Is Power BI Copilot worth turning on, and what it needs first
Power BI Copilot can write DAX, summarise reports and build visuals from a prompt, but whether that saves your team meaningful time depends almost entirely on how mature your semantic model is underneath it. The feature is real; the value is conditional.
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