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For years, we’ve treated data quality as an analytics problem, heaving dirty data over the fence to the data team to be cleaned up later in the data warehouse or lake.
This approach doesn’t work for AI. GenAI applications operate in real time, making decisions on the fly. If your data is wrong, incomplete or poorly structured, AI won’t fix it. It’ll just make bad decisions faster.
This is why data modeling has to shift left.
You can’t wait until the analytics layer to enforce data quality when AI agents need to reason, plan and act…
