Data Engineering for AI-Ready Businesses: Building Pipelines That Don't Break
Every AI initiative that fails to deliver traces back to the same root cause more often than teams like to admit: the data wasn't ready. Not the model, not the use case, the data. Messy schemas, pipelines that silently drop records, inconsistent formats between systems that were never designed to talk to each other. Data engineering is the unglamorous work that makes everything downstream, from...
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