#data-integrity

An organisation chart that changes by regulation is still master data for relational records. I keep it in SQL as a table that points at itself, with versions per agency and effective dates, read it with one query and recursive CTEs, and leave drawing it to the interface.

Money crosses every layer of my systems: database, services, JSON, browser and printed documents. I keep one convention everywhere — amounts are integers in the currency's minor unit, as ISO 8583 carries them, named with a suffix, rounded in one place and converted only at the edges.

Salary tables, salary steps, promotion, retirement age and allowances are set by regulations that keep changing. I read the regulations themselves, store what they change as data with an effective date, and keep the arithmetic in code that cites its legal basis.

A personnel database that never enforced its rules had to become clean data for a new system while the old one kept running. Ordered, repeatable phases behind a read-only door, explicit maps, honest placeholders and a report instead of a crash made that possible.

Templates come from real stacks, and copies quietly carry their data, keys, open databases and root-owned paths. My database, object storage and application generators leave the old data, keys and access behind, and read each application's facts from the application itself.

A 4 GB GPU pushed the heavy work onto a borrowed Colab runtime, so a laptop and that runtime had to share one store. Storing the data was easy. Believing it was not: seven of the ten obstacles were successes that were false, and the most useful fix removed an entire layer.