DP-600 · Question #196
You have a Fabric warehouse that contains a table named Table1. Table1 contains three columns named SalesAmount, ProductCategory, and TransactionDate. You need to create a Microsoft Power BI query…
The correct answer is B. For the TransactionDate column, select Keep top rows and set Number of rows to 90. D. For the ProductCategory column, select Group by and sum the SalesAmount column. D is correct because 'Group by' on ProductCategory with a SUM aggregation on SalesAmount is the direct operation needed to calculate total sales per category - this is the core transformation the question requires. B is correct because 'Keep top rows' set to 90 approximates one…
Question
You have a Fabric warehouse that contains a table named Table1. Table1 contains three columns named SalesAmount, ProductCategory, and TransactionDate. You need to create a Microsoft Power BI query that will calculate the total sales amount of each product category for transactions that occurred during the last quarter. Which two actions should you perform in the visual query editor? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Options
- AFor the TransactionDate column, select Remove duplicates.
- BFor the TransactionDate column, select Keep top rows and set Number of rows to 90.
- CFor the TransactionDate column, select Filter rows and set the value to last quarter.
- DFor the ProductCategory column, select Group by and sum the SalesAmount column.
- EFor the SalesAmount column, select Transformation number column - Standard, select Add,
How the community answered
(41 responses)- A10% (4)
- B71% (29)
- C5% (2)
- E15% (6)
Explanation
D is correct because 'Group by' on ProductCategory with a SUM aggregation on SalesAmount is the direct operation needed to calculate total sales per category - this is the core transformation the question requires. B is correct because 'Keep top rows' set to 90 approximates one quarter of daily transaction data (~90 days), provided the data is sorted by TransactionDate in descending order first, scoping the dataset to the last quarter before grouping. C is a common distractor: while 'Filter rows' sounds intuitive for date filtering, the visual query editor in this context does not expose a built-in relative 'last quarter' date filter option as a simple selection. A (Remove duplicates on TransactionDate) would corrupt the transaction data by eliminating legitimate same-day transactions. E (Standard Add on SalesAmount) adds a constant value to each row rather than aggregating totals.
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