Chat with Snowflake data using approved business definitions

Choose the role before the prompt

Have the warehouse owner identify the approved role and objects for the evaluation. Snowflake's access model is part of the source boundary. A privileged test credential can prove connectivity while saying little about the business user's intended access.

Use a limited approved population and record the source refresh time. A query executed now can read data loaded earlier. Keep that distinction visible when comparing the answer with an operational application.

Choose a metric with an owner

Name the calculation, period, dimensions, exclusions, and missing-value treatment. If a metric is already approved, use that definition. If two teams disagree, make the ambiguity part of the evaluation rather than silently selecting one interpretation.

For a cross-source question, validate customer identifiers and the grain of each dataset before combining results. A one-to-many join can duplicate amounts even when every individual source value is correct. Treat mapping and coverage as explicit review items.

Evaluate the operating envelope

• CorrectnessCompare the result and a representative breakdown with an approved reference under the same role and filters.
• CoverageIdentify partial results, unavailable fields, and unmatched records. Do not present a bounded sample as a full population.
• Performance and costMeasure the complete application path and inspect source-query behavior using the organization's approved monitoring. A fast model response alone does not establish an efficient warehouse workflow.

Bring a bounded question set

Prepare one ordinary metric question, one follow-up that changes the period, and one permission-sensitive request. Include the source and metric owners. The demonstration should establish a supported configuration and clear limitations; it should not promise a universal performance or accuracy number.