Commodores to Cloud ... 

A Practical Mind in a Digital Age

⚙️ My Journey in Applied Computing

My career in applied computing began in the late 1970s, bent over a clunky Commodore desktop—the model long forgotten, but the moment formative. A determined careers officer nudged me toward a college open day, where someone asked why I was interested in computers. I gave the only answer I had: a school friend, Gus, once showed me that if you followed a manual precisely, the machine responded exactly as promised. That kind of precision captivated me—even if, at the time, the usefulness wasn’t yet clear.

What was clear was my instinct to create. I wanted to build things—things that mattered. Systems that did something. Tools that helped people. Ideas that had staying power.

Fortunately, Professor Webb saw something in me and offered a place on his course. That simple act of recognition gave me direction—and launched a career rooted in the intersection of technology and real-world utility.

Since then, my work has remained grounded in one principle: technology should serve a purpose. Whether extracting meaningful insights from data, integrating complex systems across organisations, or shaping early telecom standards, my focus has always been practical. Real problems. Real people. Real impact.

In truth, I believe we’re still solving the same essential challenges as ever—only with different tools. We’ve exchanged ledgers for cloud platforms and handwriting for code, but the intent remains:

  • To chronicle
  • To compose
  • To communicate

In that sense, we’re not far removed from the Renaissance—just operating through a different set of tools; or perhaps we are just in another iteration of the Renaissance.

I often think of Gordon Urquhart from Local Hero (1983): the accountant, publican, and postmaster who quietly holds his village together. Fictional, yes—but also a fitting symbol of the mindset I value most: interdisciplinary, quietly transformative, and fundamentally human. It’s that way of thinking that shapes and powers my mindset.

💾 From Gut Feel to Ground Truth: Why Data-Centric Thinking Isn’t Optional Anymore

There was a time when projects ran on instinct, influence, and what worked “last time.” Data, if it turned up at all, was patchy, late, and argued with itself. The non-data-centric (ND) method was more about who had the strongest opinion than the clearest insight.

But even back then, a few early data rebels were starting to ask awkward questions: “Where’s the source?”, “Why doesn’t this match finance’s numbers?”, “Can we measure that—or are we just hoping?” They weren’t trying to be difficult. They were trying to make things work.

Fast forward, and we’ve (mostly) moved on. The shift to data-centric (DC) thinking means designing for clarity, traceability, and decision-making you can stand over. It’s not just about collecting data — it’s about building systems, teams, and governance models that trust it and use it.

If your project’s still running on vibes and versionless spreadsheets, it’s not agile — it’s Jurassic. 

The meteor has landed. And yes, it brought its own metadata!

My approach is grounded in four interconnected domains: structured Data, effective Governance, scalable Cloud architecture, and applied AI/ML for insight and automation. Not so much a polymath, more just T-shaped.

This site is part skills showcase, part troubleshooting manual. Basically, if my brain had a user guide, this would be the first draft.

🔧 How I Work

I combine delivery focus with architectural depth—bridging the gap between technical implementation and business value.

Whether the brief is clear or evolving, I bring structure to complexity, aligning stakeholders, developers, and analysts around shared goals. My approach is grounded in Agile principles, shaped by decades of hands-on experience across EAI integrations, ERP migrations, data platforms, and analytics programmes.

🧭 Start with Clarity

  • I establish a shared understanding of scope, objectives, and constraints—whether through a backlog, WBS, or data blueprint.
  • I facilitate early alignment sessions to surface unknowns and define success metrics that matter to both business and IT.

🔄 Deliver in Iterations

  • I lead Agile delivery using Scrum, Kanban, or hybrid frameworks—tailored to team capability and stakeholder rhythm.
  • I drive sprint planning, retrospectives, and reviews that actually improve team velocity and stakeholder confidence.

📊 Model What Matters (iteratively)

  • Data first blueprints: I lead with data—defining core entities, relationships, and timelines to shape reporting and automation.
  • Data processing blueprints: I derive the processes that use and change the data —what gets created, read, updated, or deleted (CRUD) as part business as usual.
  • Realising the blueprints: I work with devs and analysts to construct grounded, usable logical and physical models—star schemas, SCD2, DFDs, UML, BPMN, the lot.
  • Communicate to the non-tech stakeholders, I use stories, metaphors, and plain English to ensure understanding.

🔌 Connect Systems and Teams

  • I act as a translator between business SMEs, functional consultants, and technical delivery teams—bridging ERP/BSS/OSS e.g., Workday, Oracle, Snowflake, and Databricks.
  • I ensure data flows aren’t just technically integrated, but semantically aligned and auditable.

🚦 Manage Risk Proactively

  • I maintain live RAID logs, track dependencies, and surface blockers early.
  • I create delivery governance structures that scale—from squad-level standups to steering group reporting.

🧠 Build Understanding

  • I document as I go—blueprints, mapping sheets, glossary terms, or lineage diagrams. No black boxes.
  • I mentor team members, demystify architecture for business users, and leave behind capability—not just code.

If your project needs clarity, momentum, or a data-led delivery partner, I can help.