Tell me about a time you had to work with non-technical stakeholders (e.g., business or operations teams) to clarify data requirements for an SQL report or dashboard. How did you collect requirements, handle misunderstandings about the data, and ensure the final query/results met their needs?

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VirtualInterview.AI · Accepted Answer

In my last internship, our operations manager wanted a “daily fulfillment accuracy dashboard” from our orders database. Initially, the request was vague: she asked for “error rates by warehouse.” I set up a 30‑minute working session with her and a team lead and walked through a simple mockup in Google Sheets. That’s when we realized they were mixing up canceled orders, returns, and picking errors as one metric.

I translated their terms into precise definitions: a fulfillment error was an order shipped with wrong item or quantity, excluding cancellations and customer‑initiated returns. I validated this by pulling a 7‑day sample (about 12,000 orders) and walking through three real orders with them.

Once we aligned on definitions, I wrote the SQL using CASE expressions and date filters, then sent them a pilot dashboard with three warehouses and a two‑week range. After one feedback loop, they approved it, and they later used it in weekly ops meetings, cutting picking errors by about 15% in a month.

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