What causes bad data in enterprises?

Data entry slop, migrations gone wrong, encoding glitches, legacy truncations, network corruption. Multiply by millions — boom, $12.9M gone.

Do data quality tools like Monte Carlo really work?

They detect anomalies fast, no manual rules. But repair? Still on you. Hype meets reality.

Start with Gartner's $12.9M avg. Audit completeness, accuracy. Model revenue leaks from failures. Ouch incoming.

⚙️ DevOps & Platform Eng

Bad data isn't sloppy admin work. It's a $12.9 million annual revenue vampire, fangs deep in your enterprise veins.

DevTools Feed Apr 11, 2026 3 min read

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#Great Expectations #Monte Carlo #bad data costs #data observability #data quality

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Originally reported by dev.to