Always state your assumptions and confidence level. "Based on available data, I am 70% confident that X, but we could improve this by collecting Y" shows intellectual honesty.
Best answers show: transparency about data limitations, using multiple data sources to triangulate, sensitivity analysis to test how conclusions change with different assumptions, clearly communicating confidence levels, and recommending data collection to fill gaps. They should never present uncertain findings as certain.
Crucial skill. Real-world data is never perfect. Analysts who wait for perfect data never deliver. Those who pretend incomplete data is complete are dangerous. Look for the balanced, transparent approach.