Practice — Hot · The VP's Two Claims

Skills focus. Everything from this lesson, pointed at an open question: using visuals as evidence, and saying precisely what the data does and does not support.

Ungraded. No step-by-step — you choose the visuals. The solution shows one good path, not the only one.

Scenario

In Monday's meeting, the merchandising VP makes two confident claims while planning next year:

Claim 1. "December is our biggest month — it always is in retail. We staff up and stock up for the holidays, and next year we should push that even harder."

Claim 2. "Furniture is our biggest category, so it should get the most floor space in every store."

You have l01_retail_2025.csv and one lesson of Power BI. Your job is not to be right — it is to bring evidence. Build whatever visuals you need to evaluate both claims, then write a three-to-five sentence recommendation a VP would actually read.

Requirements

Evaluate Claim 1 with at least one visual. If the claim is wrong, your evidence should show by how much — and be ready for the follow-up question: why is the calendar shaped this way? (A slicer will help you answer it.)
Evaluate Claim 2 with at least two visuals that measure "biggest" two different ways.
Write the recommendation. Rules: every number in it must come off your canvas, and if two measures disagree, say so instead of picking one silently.

Hint — Claim 2 feels true; what would even challenge it?

"Biggest" in dollars is one question. The lesson's data also holds Quantity. Floor space displays items; a category selling many small items makes a different claim on shelving than a category selling few large ones. Build revenue by category and quantity by category side by side and see whether they crown the same winner.

Reflection

Which of the two claims would have survived if you had only ever built revenue charts?
What data that is not in this file would you want before making a real floor-space decision? Name two things.