Poor data quality costs organizations $12.9M per year on average. Prevention costs 1%.
Gartner: poor data quality costs organizations $12.9M/year on average. Causes: missing validations, schema drift, upstream changes, and stale data.
Prevention costs: data quality monitoring ($20-50K/year), schema validation ($10-20K), data contracts ($15-30K engineering time). Total: $45-100K. ROI: 100-280x.
Implement: Great Expectations, dbt tests, Monte Carlo, or Soda. Any of these pays for itself within the first quarter.
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8 minPublished Work
This article expands on ideas from my published work in CIO.com, Built In, Mind the Product, and HackerNoon. View published articles →
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