A Direct Lake report briefly combines new sales with old customer data during ETL. Would you prioritize freshness or a consistent reporting batch?

Instruction: Senior-level, open-ended case. Several approaches can be defensible; explain your assumptions, recommendation, tradeoffs and what evidence would change your choice. Explain whether your audience accepts provisional data and how the upstream batch is published. Do not describe disabling automatic updates as a cross-table transaction guarantee or assume every Direct Lake query is constrained to the frame. For a mock interview, allow two minutes for your first answer, then 30 seconds to respond to the pressure-test twist. State what changed, your next action and what you cannot safely promise.

Context: This open-ended senior case assesses decision quality. Treats freshness and consistency as explicit product choices, distinguishes framing from upstream orchestration, and checks a fallback path that can undermine the intended reporting snapshot.

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The first question is whether this is an operational monitor or a report people use to close the books. An operational team might accept briefly provisional figures for lower latency. Finance may require sales and customer classifications from one validated batch. Those are different products, even if they use the same tables. For the operational case, automatic Direct Lake updates can be reasonable, with visible freshness information and checks for unacceptable mismatches...

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