Natural Language Is a Data Interface, Not a Substitute for Semantic Modeling

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A two-part technical series from DEV Community explores how an Enterprise Data Discovery Assistant enables business users to query a Customer 360 domain of over 100 million records without knowing SQL or database schemas. The system relies on Snowflake semantic views to make analytical decisions explicit, covering metrics, relationships, time semantics, and access rules, rather than letting a language model guess from raw table names. Before any query runs, the assistant performs a mandatory data-contract check to verify freshness, quality, and trustworthiness of the target data product. Depending on the contract result, the system either proceeds normally or attaches a warning if the data is stale, degraded, or failed. The core finding is that natural language broadens access to well-modeled data but does not replace the need for rigorous data modeling and governance infrastructure.

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