In the world of data, we often talk about “data products” and “data as a service.” Sounds great, right? But here’s the dirty little secret: too often, data isn’t reliable. It’s like building a beautiful house on a shaky foundation.

Imagine you’re a data consumer — perhaps a business analyst creating a critical report, or a machine learning engineer building a predictive model. You pull data from a source, only for the schema to unexpectedly change, a column to go missing, or the data quality to plummet without warning. Suddenly:

• Your dashboards break.
• Your reports show incorrect numbers.
• Your machine learning models start making bad predictions.
• You spend hours, days, or even weeks debugging data issues, not building value.

This isn’t just annoying; it erodes trust, slows down innovation, and costs organizations significant time and money. The root cause? A lack of clear, enforced agreements between data producers (those generating the data) and data consumers (those using it). This is where data contracts come in.

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