The Evolution of a Datanerd: Obsessed with Schema

Handcoding the Wild West (Where Schema Was King)

If you’ve been in Australian tech for a minute, you know the era I’m talking about. We weren’t just writing code; we were building bespoke applications, and the real thrill was designing the schema.

My first major foray was into web development for Aussie politicians, where we had the dubious pleasure of building custom databases, revelling in the raw dimensionality of a simple table structure. Yes, they were backed by Microsoft Access and fronted by ASP. Don’t judge the tools; respect the data model.

This dedication to structure grew as we architected CRMs for high-end art and wine sales. But the true masterpiece was cataloging my father’s small-town antique store for the global internet. This was my first full-scale taxonomy challenge—turning piles of real-world historical clutter into clean, structured metadata ready for global discovery.

This level of granular, hands-on data structure was refined at the feet of the masters during those early Microsoft SQL Server bootcamps (before open source made things fun). Every foreign key, every index, every normalization decision was deliberate. The schema wasn’t just a technical requirement—it was the foundation of everything.

Surviving the Cloud Shift: Performance as a Narrative

When the cloud arrived, the stakes were instantly raised. The technical problem shifted from “how to structure it?” to “how to query and visualise it fast?”

This pivot led to architecting what became one of Australia’s largest volunteering portals. The job meant wrestling complex geospatial data from a grumpy NoSQL database. This was pure data drama—the struggle to extract the geographic truth hidden inside the coordinates and present it reliably and performantly to thousands of users.

This trench warfare in high concurrency taught me that performance isn’t just speed; it’s a critical part of the data narrative. A slow dashboard isn’t just annoying—it’s a broken story. Users don’t wait for insights; they need them now. The cloud promised infinite scale, but it demanded a new level of thinking about query optimization, caching strategies, and real-time data flows.

The lesson was clear: beautiful schemas are worthless if the queries can’t deliver answers at the speed of thought.

The Datanerd Rises: Building the Perfect Infographic

The transition to Big Data felt like moving from drawing charts by hand to conducting a massive, automated orchestra.

I evolved into data and analytics engineering, leaving the brittle bespoke trenches behind to build robust, reliable pipelines that transform chaotic source data into clean, ready-to-visualise models. We cover the entire BI spectrum: from rapid narrative testing using the free, versatile version of Looker Studio (the Swiss Army knife of data storytelling), all the way to implementing and optimising the full-stack power of Looker.

The goal is always the same: architect the perfect infographic that drives strategic action.

Because here’s the truth: a database is just potential. A perfectly normalized schema with elegant foreign keys is beautiful, but it’s not a story. An infographic—a dashboard, a chart, a map—is the translator that turns raw structure into understanding, insight, and emotion.

It’s the difference between showing someone a table of sales figures and showing them a visual narrative of growth, risk, and opportunity. The data was always there. The infographic makes it sing.

Community, Clarity, and Continuous Discovery

This lifelong evolution is fueled by the community that helps us stay sharp, clear, and continuously curious.

For technical inspiration and clarity on industry trends, the (Analytics Power Hour Podcast)[https://analyticshour.io/] is a constant source of insight (and occasional laughter). For connecting with the local Sydney community and sharing technical war stories, the Data & Analytics Wednesday meetups have been invaluable. And nothing quite brings the energy and hands-on learning like participating in the annual unconference, Measure Camp Sydney.

These communities remind us that data work isn’t a solo pursuit. The best schemas, the cleverest queries, the most beautiful dashboards—they all come from shared knowledge, honest feedback, and the occasional heated debate over whether star or snowflake schemas are superior (it depends, obviously).

From the Byte to the Dashboard

This full-stack journey—from praying over table definitions in Access to engineering beautiful, high-performance data models for Looker—means we understand data at every layer, from the single byte to the final dashboard.

We know what it’s like to wrestle with dirty source data at 3 AM. We’ve felt the satisfaction of a perfectly optimized query shaving seconds off a critical report. We’ve seen stakeholders’ eyes light up when an infographic finally makes the story clear.

It’s this history, and this data-obsessed perspective, that Code4.au brings to every project. Because the tools change, the platforms evolve, but the core mission remains: find the structure in the chaos, build it right, and tell the story beautifully.

The soul of a Datanerd is eternal.