The real cost of poor data architecture
This isn't abstract technical debt. This is decisions made in 2019 that cost €400k per year in 2025.
$400,000 per year. This isn't a hypothetical. It's what a data architecture decision made in 2019 — by a team under pressure, on a stack chosen because "it's what everyone uses" — costs in 2025. Not in software licensing. In wasted engineering time, operational latency, missed opportunities, and senior engineers who resigned rather than maintain a system they no longer respected.
We always talk about technical debt as an abstract concept, something you pay down "later." In data, debt isn't abstract. It measures in minutes of dashboard loading time, in pipelines that fail every Monday morning, in ML models training on data whose freshness nobody can guarantee anymore.
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