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Data Infrastructure

The Pipeline Blindspot: Why Great Models Fail With Bad Data Infrastructure

ServicesOctober 27, 20256Views0Likes0Comments
The data science team spent six months building a fraud detection model with 96% accuracy on test data. The board approved a million-dollar investment. Production launch went smoothly with no technical errors. Three months later, the model catches only 68% of actual fraud cases while flagging legitimate transactions at triple the expected rate. The data scientists review their…

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Data Warehouse

Why Your Data Warehouse Costs Keep Exploding (And How to Fix It)

ServicesOctober 23, 20258Views0Likes0Comments
The CFO walks into the Monday morning meeting holding a printed report. The data warehouse bill jumped from $15,000 to $47,000 last month. The analytics team scrambles to explain. They review usage logs, check for anomalies, and examine query patterns. Everything appears normal. Teams are running the same reports, processing similar data volumes, and conducting routine analyses.…

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Data Engineering

Why 67% of AI Models Fail in Production (And How Data Engineering Prevents It)

ServicesSeptember 15, 202525Views0Likes0Comments
The boardroom presentation was flawless. The AI model predicted customer churn with 94% accuracy, identified fraud patterns with precision, and promised to save millions annually. Six months later, the same model sits disabled in production, its predictions so wildly inaccurate that the customer service team stopped trusting its recommendations. The company joins the 80% of organizations whose…

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