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Practical perspectives on data governance, Microsoft Fabric, Power BI and analytics strategy for UK organisations.
Power BI Changes Need A Release Process. Most Teams Don't Have One.
Most Power BI estates have no formal release process. Here is what a proper CI/CD process for Power BI and Fabric actually looks like.
Row-Level Security Looks Simple. That's How It Fails.
Row-level security is easy to demo and easy to get quietly wrong in production. Here is how RLS actually behaves at scale, where teams get caught out, and how to test it properly before real users see the wrong rows.
Microsoft AI Isn't One Product. It's Five Decisions.
Most people hear "Microsoft AI" and think Copilot. It's actually five distinct tools, each built for a different job. Here's a practical way to decide which one fits the problem in front of you.
Governance in practice: what actually has to exist before AI touches your data
Governance is not a policy document. It is agreed metric definitions, clear ownership, documented lineage, sensible access controls and a change process, all of it tested against what an AI feature actually needs before you deploy one.
Your data is in good shape. That does not make you AI-ready.
A clean, governed data estate is necessary for AI. It has never been sufficient. Here is the difference between data readiness and AI readiness, and why the gap between them is where most projects stall.
Why we backed Pyramid, and what makes it such a strong platform
A proud look back from the partner who knew it best. What Pyramid did exceptionally well, and why ServiceNow buying it confirms what we saw in 2024.
Are you AI-ready? A four-week assessment framework for mid-market analytics
Most AI readiness talk stays vague. Ours is a four-week, fixed-price assessment that scores your data foundations against AI-readiness and hands you two or three costed use cases, or an honest recommendation to wait.
The end of the visual hack
The clever workarounds that bent Power BI into shape are on their way out. That is a relief, and also a quiet warning.
What happens after go-live: hypercare, Continuity and keeping analytics governed
Go-live is not the finish line. Heres how we run the stabilisation window straight after launch, and what Continuity actually covers once a platform settles into business as usual.
How to Use AI to Improve Sales: A Practical Plan You Can Actually Implement
A practical, no-hype plan for using AI to improve sales performance, from lead scoring and pipeline forecasting to Copilot-assisted selling, and the guardrails to put in place before you roll it out.
Orchestration Is Not Scheduling. It's How Pipelines Survive At Scale.
A green tick on a pipeline run tells you it finished. It does not tell you it scaled safely, recovered from a partial failure, or protected downstream reports from a bad batch. Here is the orchestration pattern that separates fragile pipelines from ones that hold up under real load.
Fixed price, not time and materials: how we scope and price analytics work
Most fixed-price analytics quotes are a guess dressed up as a number. Heres what we document before we will put a firm price on a Build phase, and when a day-rate arrangement genuinely serves you better.
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