Despite the explosion of 'talk to your data' agents, most fall short of production-grade accuracy — here's why the problem is architectural, not just about better LLMs.
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Not all AI agent data integration approaches deliver the same results. Compare 5 patterns—from direct API calls to AI-native data fabrics—across accuracy, governance, deployment speed, and cost.
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AI agents require fundamentally different data architecture than traditional BI. This comparison examines performance, cost, and governance differences—plus real deployment timelines.
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Data virtualization isn't replacing ETL or data warehouses — it's solving different problems. Understand when to use virtualization, federation, ETL, warehouses, lakes, and data fabric.
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