Flat analysis CSV
24 joined records with calculated revenue, cost and profit. Works in Excel, Tableau and Power BI.
Public downloadOpen practice
Use a small fictional TrailPeak dataset to calculate recorded sales, compare categories, and explain one finding. No sign-in is required. Allow 30–45 minutes.
TrailPeak is fictional practice data. One Orders row is an order record. Product prices and costs live in Products; store region lives in Stores. The returned flag does not specify a refund amount, so the calculations below describe recorded sales before a separately modeled refund adjustment.
24 joined records with calculated revenue, cost and profit. Works in Excel, Tableau and Power BI.
Public downloadOrders, Products and Stores tables for repeatable SQL queries.
Public downloadSix runnable queries with expected checks and limitations.
Public downloadSELECT COUNT(*) AS Order_Rows,
COUNT(DISTINCT Order_ID) AS Distinct_Orders
FROM Orders;Connect Tableau or Power BI to the flat CSV. Use one bar chart of revenue by Category, one of profit by Category, and a Channel filter. Add a title that names the question and the period covered by the file. Reconcile totals before formatting.
Check the question: Revenue ranks sales volume in dollars; profit ranks the difference between recorded revenue and cost. They can support different decisions. This small practice file does not establish demand forecasts or causal effects.
| Check | Expected result |
|---|---|
| Order records and distinct order IDs | 24 and 24 |
| Units | 102 |
| Recorded revenue | $10,869.55 |
| Recorded cost | $5,707.00 |
| Recorded profit | $5,162.55 |
Keep the input file, formulas or query, one chart, the reconciled totals, and a short claim with its limitation. If you use AI, record the prompt, the part you accepted, and how you checked it. Never upload confidential student or company data to an unapproved tool.
See the full course map or apply TRACE to the next question.