Building an Agent-Ready Data Warehouse: What Traditional Architectures Do Wrong
Towards Data Science
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Traditional data warehouses are designed for human oversight but struggle to support AI agents that autonomously interpret data and make decisions without embedded business rules. While warehouses centralize data and metadata, they lack explicit definitions of business metrics and rules, leading AI agents to potentially recommend incorrect actions despite accurate data queries.
