A lot gets written about data quality, and very little gets measured. The German-language practitioner’s standard reference alone lists sixty possible quality criteria — from timeliness to reliability —, and even the lean models still arrive at six to fifteen dimensions. Yet the core of the matter is surprisingly tangible: a data error caught during … Read more
The conventions were settled: procedure skeletons, DECLARE banners, file naming, forbidden constructs — all versioned in rule files, every rule with its rationale. The only open question was which tool should check the SQL conventions. And the first reflex was the same one that probably surfaces in every Postgres team with convention ambitions: “Just use … Read more
Most data quality systems don’t die of bad checks. They die of a missing field in the rule model: the severity. A missing country code in three out of 80,000 rows blocks the nightly load, someone switches the check off “temporarily”, and from that moment everything runs unchecked. Steering data quality with severity levels instead of binary … Read more
The rule “country_code is mandatory” lives in your database twice: once as NOT NULL in the target table’s schema, and once as a hand-typed row in the check configuration. On the next ALTER TABLE, only one of the two places changes, and the check silently goes wrong. With derived data quality rules you no longer type that repetition: the metadata already … Read more
There is a moment when a CLAUDE.md tips over. That moment does not sit on any calendar, it shows in behavior: the file keeps getting longer, and the rules inside it keep getting followed less. Every new convention you write in dilutes the ones already there. That is exactly where the project behind this article … Read more
It didn’t start with an audit. It started with a nagging feeling: the interface looked restless. You don’t notice it at first glance, but on the second and third look it is there — a timestamp slightly larger here than there, a dialog title a touch smaller than in the neighboring dialog. Everyone knows the … Read more
SQL Server or PostgreSQL — the question is rarely “which database is better?” but “which one fits your budget, your team and your platform?”. Whoever confuses the two questions migrates for the wrong reasons and only notices once the licensing bill shrinks while operating costs grow. Quick overview: Prerequisite: Hands-on SQL Server experience is all you … Read more
“You spend more time with her than with me.” That’s a sentence you usually hear when an affair comes to light — in my case, it was about Claude Code. And suddenly there was a question in the room I had never thought about before: Is Claude actually a woman or a man? What this … Read more
An empty repo and Claude Code, Anthropic’s coding agent in the terminal — that’s all it takes to get going. And that is exactly the problem: the model writes code immediately, but by default nothing ensures that a specification exists first, that a review happens afterwards, or that the database schema deploys reproducibly. A Claude … Read more
In many projects the database schema lives in the database instead of the repository — grown out of years of hand-run ALTERs, fully documented nowhere. It only becomes visible when a second environment is needed or a deploy breaks. Postgres database CI/CD flips that relationship: the repository describes the desired state, and every environment — from the throwaway … Read more
The bug was a typo in an ALTER TABLE — and it was found by the staging deploy on a Friday afternoon. Yet that exact find is automatable: set up a GitHub Actions Postgres deployment against a throwaway database, and every pull request becomes a full dress rehearsal. Syntax and semantic errors, ordering problems, and broken idempotency surface before … Read more
