Writing
Data engineering, platform architecture, and practical automation. Judgement and trade-offs, not tutorials.
-
What Makes a Data Platform AI-Ready Before Anyone Adds an LLM
Most organisations chase AI adoption by bolting models onto fragile pipelines. The real work is upstream — data quality, lineage, contracts, and governance that make AI possible without making it dangerous.
-
Designing Data Platform Architecture for the Team You'll Have in Two Years
Most data platform architecture is designed for the team that exists today. That's a problem, because in two years the team will be bigger, the requirements will be different, and the shortcuts will be load-bearing.
-
Why Your dbt Project Will Become Unmaintainable
dbt makes it easy to start a data transformation layer. It also makes it easy to build one that nobody can reason about six months later. These are the patterns that rot.
-
Test Harnesses for Data Pipelines: Engineering Confidence at Every Layer
Testing data pipelines isn't like testing application code. The inputs are messy, the outputs are probabilistic, and the infrastructure is expensive. Here's how to build test harnesses that work.
-
Data Quality Gates That Actually Work in Production
Most quality gates either fire so often they get ignored or sit silently while bad data flows downstream. Here's how to build gates that catch real problems without crying wolf.
-
When Your Data Warehouse Needs a Second Act
Every data warehouse I've joined was already overdue for redesign. The signals are consistent, the migration path is well-known, and the biggest risk is waiting too long to start.
-
The OPC Timestamp Gotcha That Silently Shifts Your Entire Historian Dataset
When a PLC stores timestamps in local time and the OPC server assumes UTC, every data point in your historian is wrong by your timezone offset. It gets worse during daylight saving transitions.
-
The Maximo Integration That Stopped Sending Data and Nobody Noticed for Six Weeks
IBM Maximo's MIF outbound queue can die silently — no error log, no alert, no notification. Here's how it happens and how to build monitoring that catches it.
-
Your PI Historian's Compression Settings Are Silently Destroying Your Analytics
OSIsoft PI's swinging door compression is brilliant for storage. It's also silently eating the data points your downstream analytics need to produce correct averages, totals, and trends.
-
SAP PM Counter Overflow and the Haul Truck That Got Maintained Twice
When an equipment hour counter resets at its overflow boundary, SAP PM's maintenance scheduling calculates a negative usage delta. The consequences for a mining fleet are worse than you'd think.
-
Ellipse to Maximo Migration: The Equipment Hierarchy Problem Nobody Warns You About
Migrating from Mincom Ellipse to IBM Maximo in a mining operation sounds like a data mapping exercise. It's actually an ontological argument about what an asset is.