Explanation:
The measure should use the AVERAGE function to calculate the average value.
It should reference the Response Value column from the ' Survey ' table.
The ' Number of months ' should be used to define the period for the average calculation.
To calculate the average overall satisfaction score using DAX, you would need to use the AVERAGE function on the response values related to satisfaction questions. The DATESINPERIOD function will help in calculating the rolling average over the last 12 months.

Explanation:

Explanation:

We are analyzing this KQL query:
Sales
| where Status != " Cancelled "
| where OrderDate > = ago(30d)
| summarize TotalSales = sum(SalesAmount) by ProductCategory
| where TotalSales > 0
Statement 1:
" The query excludes sales that have a Status of Cancelled. "
Yes # where Status != " Cancelled " filters them out.
Statement 2:
" The query calculates the total sales of each product category for the last 30 days. " Yes # where OrderDate > = ago(30d) ensures only last 30 days.
summarize TotalSales = sum(SalesAmount) by ProductCategory groups by category.
Statement 3:
" The query includes product categories that have had zero sales during the last 30 days. " No # The final filter where TotalSales > 0 excludes categories with zero sales.
Final Answer:
Excludes Cancelled sales # Yes
Calculates total sales by product category for last 30 days # Yes
Includes product categories with zero sales # No
References:
KQL where operator
KQL summarize operator

Explanation:

Explanation:

For the Customers table, where the requirement is to create a new version of the row, you would use:
Type 2 SCD: This type allows for the creation of a new record each time a change occurs, preserving the history of changes over time.
For the Products table, where the requirement is to overwrite the existing value in the latest row, you would use:
Type 1 SCD: This type updates the record directly, without preserving historical data.